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Research Handbook of Financial Markets (Hardcover): Refet S. Gürkaynak, Jonathan H. Wright Research Handbook of Financial Markets (Hardcover)
Refet S. Gürkaynak, Jonathan H. Wright
R6,707 Discovery Miles 67 070 Ships in 12 - 17 working days

The Research Handbook of Financial Markets carefully discusses the histories and current states of the most important financial markets and institutions, as well as explicitly underscoring open questions that need study. By describing the institutional structure of different markets and highlighting recent changes within them, it accurately highlights their evolving nature. Taking the perspective that finance and macroeconomics are intertwined, this illuminating Research Handbook brings together prominent experts to investigate key market interactions. Chapters act as self-contained case studies of particular markets, allowing for a thorough individual examination of each. Ultimately, they offer a holistic understanding of financial markets and the current state of research. Academics and researchers in economics and finance curious about developments within financial regulation and banking will find this comprehensive Handbook to be hugely valuable. Market participants will additionally find it to be a useful reference, along with regulators seeking to mitigate financial instability.

International Finance Discussion Papers - Exact Confidence Intervals for Impulse Responses in a Gaussian Vector Autoregression... International Finance Discussion Papers - Exact Confidence Intervals for Impulse Responses in a Gaussian Vector Autoregression (Paperback)
Jonathan H. Wright
R363 R292 Discovery Miles 2 920 Save R71 (20%) Ships in 10 - 15 working days

Many techniques have been proposed for forming confidence intervals for the impulse responses in a vector autoregression. However, numerous Monte-Carlo simulations have shown that all of these methods often have coverage well below the nominal level. This paper proposes a new approach to constructing confidence intervals for impulse responses in a vector autoregression, making the additional assumption of Gaussianity. These confidence intervals are conservative in all sample sizes; by construction they have coverage that must be greater than or equal to the nominal level.

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