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on Financial Markets |
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Issue of 2017‒11‒19
three papers chosen by |
| By: | Esteve García, Vicente; Navarro Ibáñez, Manuel; Prats Albentosa, María Asuncíon |
| Abstract: | According to several empirical studies, the Present Value model fails to explain the behaviour of stock prices in the long-run. In this paper, the authors consider the possibility that a linear cointegrated regression model with multiple structural changes would provide a better empirical description of the Present Value model of U.S. stock prices. The methodology is based on instability tests recently proposed in Kejriwal and Perron (The limit distribution of the estimates in cointegrated regression models with multiple structural changes, 2008, and Testing for multiple structural changes in cointegrated regression models, 2010) as well as the cointegration tests developed in Arai and Kurozumi (Testing for the null hypothesis of cointegration with a structural break, 2007) and Kejriwal (Cointegration with structural breaks: an application to the Feldstein- Horioka Puzzle, 2008). The results obtained are consistent with the existence of linear cointegration between the log stock prices and the log dividends. However, the empirical results also show that the cointegrating relationship has changed over time. In particular, the Kejriwal-Perron tests for testing multiple structural breaks in cointegrated regression models suggest a model of three or two regimes. |
| Keywords: | present value model,stock prices,dividends,cointegration,multiple structural breaks |
| JEL: | C22 G12 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:201793&r=fmk |
| By: | Biqing Cai; Jiti Gao |
| Abstract: | In this paper, we propose a simple approach to testing and modelling nonlinear predictability of stock returns using Hermite Functions. The proposed test suggests that there exists a kind of nonlinear predictability for the dividend yield. Furthermore, the out-of-sample evaluation results suggest the dividend yield has nonlinear predictive power for stock returns while the book-to-market ratio and earning-price ratio have little predictive power. |
| Keywords: | Hermite functions, out-of-sample forecast, return predictability, series estimator, unit root. |
| JEL: | C14 C22 G17 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:msh:ebswps:2017-18&r=fmk |
| By: | Gupta, Abhimanyu; Kokas, Sotirios; Michaelides, Alexander |
| Abstract: | A large theoretical literature emphasizes the importance of financial networks, but empirical studies remain scarce. Due to overlapping bank portfolios, the syndicated loan market provides a natural setting to study financial networks. We exploit the tiered structure of syndicated loans to construct such a network and characterize quantitatively its evolution over time. A spatial autoregressive model provides an ideal methodological framework to estimate spillovers from this financial network to lending rates and quantities. We find that these spillovers are economically large, time-varying and can switch sign after major economic shocks. Moreover, we find that network complexity and uncertainty rise after a large negative shock. Counterfactual experiments confirm the quantitative importance of spillovers and network structure on lending rates and quantities and can be used to disentangle the effects arising from spillovers versus changes in network structure. |
| Keywords: | complexity.; cost of lending; Financial Networks; spatial autoregression; Spillovers; syndicated loan market |
| JEL: | G01 G21 L14 |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12424&r=fmk |