Recent research by Giglio, Kelly and Kozaz (2020) empirically analyzes a large cross-section of equity returns to estimate a rich affine model of equity prices, dividends, returns and their dynamics. By constructing a model, they price dividend strips of the aggregate market index, as well as any other well-diversified equity portfolio. As matter of fact, they first validate the predictions of the model for the discount rates of risky cash flows by comparing the implied dividend strips from the same model to the prices of actually traded dividend strips (from Bansal et al. (2017) and van Binsbergen and Koijen (2015)), matching well the prices of observed dividend strips on the S&P500 since 2004. Then, they use the model to explore the properties of implied dividend strips extending the time series back to the 1970s, and studying the cross-section of term structure of different portfolios. Indeed, the new term structure data generated represents new empirical moments that can be used to guide and evaluate asset pricing models. Starting from this paper, I analyze the literature concerning the term structure of equity in theoretical and empirical research, and then I combine the same cross-section of equity yields with 5 macroeconomic data, coding in Python and using Project Jupyter, in order to investigate the predictive role of the variables.
Rendimenti azionari trasversali e la macroeconomia
FATALE, MATTEO
2019/2020
Abstract
Recent research by Giglio, Kelly and Kozaz (2020) empirically analyzes a large cross-section of equity returns to estimate a rich affine model of equity prices, dividends, returns and their dynamics. By constructing a model, they price dividend strips of the aggregate market index, as well as any other well-diversified equity portfolio. As matter of fact, they first validate the predictions of the model for the discount rates of risky cash flows by comparing the implied dividend strips from the same model to the prices of actually traded dividend strips (from Bansal et al. (2017) and van Binsbergen and Koijen (2015)), matching well the prices of observed dividend strips on the S&P500 since 2004. Then, they use the model to explore the properties of implied dividend strips extending the time series back to the 1970s, and studying the cross-section of term structure of different portfolios. Indeed, the new term structure data generated represents new empirical moments that can be used to guide and evaluate asset pricing models. Starting from this paper, I analyze the literature concerning the term structure of equity in theoretical and empirical research, and then I combine the same cross-section of equity yields with 5 macroeconomic data, coding in Python and using Project Jupyter, in order to investigate the predictive role of the variables.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14240/152836