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We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735
This paper sheds light on the impact of global macroeconomic uncertainty on the euro area economy. We build on the methodology proposed by Jurado et al. (2015) and estimate global as well as country-specific measures of economic uncertainty for fifteen key euro area trade partners and the euro...
Persistent link: https://www.econbiz.de/10012503567
Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...
Persistent link: https://www.econbiz.de/10011604927
Based on the theory of static replication of variance swaps we assess the sign and magnitude of variance risk premiums in foreign exchange markets. We find significantly negative risk premiums when realized variance is computed from intraday data with low frequency. As a likely consequence of...
Persistent link: https://www.econbiz.de/10010410031
We examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model incorporating both time varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance...
Persistent link: https://www.econbiz.de/10013097882
We develop a simple and fast methodology for the estimation of future outstanding, discrete dividend payments, based on market prices of American at-the-money options. Our method relies on a linear combination of no-arbitrage bounds of the dividends. The corresponding optimal weight is...
Persistent link: https://www.econbiz.de/10012962365
In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...
Persistent link: https://www.econbiz.de/10012907596