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We explore mixed data sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Volatility and related processes are our prime focus, though the regression method has wider applications in macroeconomics and finance, among other...
Persistent link: https://www.econbiz.de/10005476038
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We analyze the effect of taxes and government spending on quarterly market returns of stocks, government bonds, and corporate bonds. In US data from 1960 to 2000, a one standard deviation increase in the share of tax receipts in GDP has a statistically and economically significant effect on...
Persistent link: https://www.econbiz.de/10005120795
We use data from prospectus supplements to create measures of the complexity of securitized products. We use these measures to investigate whether and to what extent complexity plays a role in the performance and pricing of mortgage-backed securities. We find that securities in more complex...
Persistent link: https://www.econbiz.de/10011081879
We propose a new approach to predictive density modeling that allows for MIDAS effects in both the first and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dynamics. When applied to quarterly U.S. GDP growth data,...
Persistent link: https://www.econbiz.de/10011083475
We propose a new approach to imposing economic constraints on time-series forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We...
Persistent link: https://www.econbiz.de/10011083895
We propose a new approach to imposing economic constraints on time-series forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We...
Persistent link: https://www.econbiz.de/10010896689
We propose a new approach to predictive density modeling that allows for MI- DAS e¤ects in both the ?rst and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dy- namics. When applied to quarterly U.S. GDP growth...
Persistent link: https://www.econbiz.de/10010891962
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