Nonparametric tail risk, macroeconomics and stock returns: predictability and risk premia

This paper proposes a new novel to calculate tail risks incorporating risk-neutral information without dependence on options data. Proceeding via a non parametric approach we derive a stochastic discount factor that correctly price a chosen panel of stocks returns. With the assumption that states probabilities are homogeneous we back out the risk neutral distribution and calculate five primitive tail risk measures, all extracted from this risk neutral probability. The final measure is than set as the first principal component of the preliminary measures. Using six Fama-French size and book to market portfolios to calculate our tail risk, we find that it has significant predictive power when forecasting market returns one month ahead, aggregate U.S. consumption and GDP one quarter ahead and also macroeconomic activity indexes. Conditional Fama-Macbeth two-pass cross-sectional regressions reveal that our factor present a positive risk premium when controlling for traditional factors.

Integrating species life-history traits and patterns of deforestation in amphibian conservation planning

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An analysis of financial and monetary cooperation in Africa

Includes bibliography

Economic policy options and financial globalization: Mexico, 1988-99

Includes bibliography

Mexico: economic growth, exports and industrial performance after NAFTA

Includes bibliography

Economic policy, institutions and productive development in Latin America

Includes bibliography

The competitive real exchange-rate regime, inflation and monetary policy

Includes bibliography

Economic development, industry and energy: report of Committee II

Incluye Bibliografía