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Supplementary Appendix to 'Modeling the Dependence of Conditional Correlations on Market Volatility'
Bauwens, Luc - 2017
/tables/figures of the paper are referenced by numbers. In Section A, we expose the estimation procedure of the models employed in the … detail the estimation method and the results behind our findings about the long-run and short-run effects of the volatility …
Persistent link: https://www.econbiz.de/10012956778
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Modeling the Dependence of Conditional Correlations on Market Volatility
Bauwens, Luc - 2017
Several models have been developed to capture the dynamics of the conditional correlations between time series of financial returns and several studies have shown that the market volatility is a major determinant of the correlations. We extend some models to include explicitly the dependence of...
Persistent link: https://www.econbiz.de/10012956782
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Realized semicovariances : looking for signs of direction inside the covariance matrix
Bollerslev, Tim; Patton, Andrew J.; Quaedvlieg, Rogier - 2017 - This version: September 5, 2017
components and the mixed-sign component load differently on economic information concerning stochastic correlation and jumps. The …
Persistent link: https://www.econbiz.de/10012116691
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Forecasting Realized Volatility Using a Nonnegative Semiparametric Model
Eriksson, Anders - 2019
its error component is partially unspecified. The statistical properties of the model are discussed and a novel estimation …
Persistent link: https://www.econbiz.de/10012863889
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Forecasting Structural Changes in Short and Long-Run Correlations : A Mixed Regime DCC-MIDAS Model
marchese, malvina; Kyriakou, Ioannis; Tamvakis, Michael; … - 2022
breaks of different type in the conditional and unconditional correlation components by capturing abrupt regime switches in … the forecasting accuracy of the correlation component models by explicitly accounting for parameter instability over time …
Persistent link: https://www.econbiz.de/10013291422
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What they did not tell you about algebraic (non-)existence, mathematical (ir-)regularity and (non-)asymptotic properties of the full BEKK dynamic conditional covariance model
McAleer, Michael - In: Journal of risk and financial management : JRFM 12 (2019) 2/66, pp. 1-7
Persistently high negative covariances between risky assets and hedging instruments are intended to mitigate against risk and subsequent financial losses. In the event of having more than one hedging instrument, multivariate covariances need to be calculated. Optimal hedge ratios are unlikely to...
Persistent link: https://www.econbiz.de/10012022157
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What they did not tell you about algebraic (non-)existence, mathematical (ir-)regularity and (non-)asymptotic properties of the Dynamic Conditional Correlation (DCC) model
McAleer, Michael - In: Journal of risk and financial management : JRFM 12 (2019) 2/61, pp. 1-9
correlation model to have been developed to date, namely the widely used Dynamic Conditional Correlation (DCC) model. Dynamic …
Persistent link: https://www.econbiz.de/10012022209
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Long memory dynamics for multivariate dependence under heavy tails
Janus, Paweł; Koopman, Siem Jan; Lucas, André - 2011
Persistent link: https://www.econbiz.de/10009720703
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Measuring Contemporaneous Correlation between Return Shock and Volatility Shock in an EGARCH Model
Yang, Minxian - 2011
measuring the contemporaneous correlation between the return shock and the volatility shock. We show that the contemporaneous … correlation can be quantified within an EGARCH model, where the composite disturbance to the return follows a normal log … the proposed model are analyzed. The estimation of the model with the SP500 excess return series lends a mild support for …
Persistent link: https://www.econbiz.de/10013133961
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Long/Short Equity Risk Premia Parity Portfolios via Implicit Factors in Regularized Covariance Regression
van Jaarsveldt, Cole; Peters, Gareth; Ames, Matthew; … - 2023
A time-series basis decomposition and trend extraction technique known as Empirical Mode Decomposition (EMD), designed for multi-scale time-frequency decomposition in non-stationary time-series settings, will be combined with Regularised Covariance Regression (RCR) methods to produce a framework...
Persistent link: https://www.econbiz.de/10014348857