Google scholar excess volatility
WebExcess Volatility in the Financial Markets: A Reassessment of the Empirical Evidence Marjorie A. Flavin University of' Virginia Numerous authors, including Shiller, LeRoy and … WebThis paper considers the optimal dividend and capital injection problem for an insurance company, which controls the risk exposure by both the excess-of-loss reinsurance and capital injection based on the symmetry of risk information. Besides the proportional transaction cost, we also incorporate the fixed transaction cost incurred by capital …
Google scholar excess volatility
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WebOct 24, 2024 · [Google Scholar] Glosten, Lawrence R., Ravi Jagannathan, and David E. Runkle. 1993. On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. Journal of Finance 48: 1779–801. [Google Scholar] Hamadu, Dallah, and Ade Ibiwoye. 2010. WebFeb 10, 2024 · A highly transmittable and pathogenic viral infection, COVID-19, has dramatically changed the world with a tragically large number of human lives being lost. The epidemic has created psychological resilience and unbearable psychological pressure among patients and health professionals. The objective of this study is to analyze …
WebSep 20, 2024 · BiFeO3 is a multiferroic material with a perovskite structure that has a lot of potential for use in sensors and transducers. However, obtaining pure single-phase BiFeO3 ceramic with a low electrical conductivity via solid-state reactions remains a problem that limits its application. In this work, the suppression of secondary phases in BiFeO3 was … WebDec 13, 2016 · CrossRef Google Scholar Fama, E. 1970. Efficient capital markets: A review of theory and empirical work. Journal of Finance 25: 283–417. CrossRef Google …
WebGoogle Scholar provides a simple way to broadly search for scholarly literature. Search across a wide variety of disciplines and sources: articles, theses, books, abstracts and court opinions. WebJan 20, 2012 · We study an investor’s asset allocation problem with a recursive utility and with tradable volatility that follows a 2-factor stochastic volatility model. Consistent with previous findings under the additive utility, we show that the investor can benefit substantially from volatility trading due to hedging demand.
WebFeb 28, 2024 · This article investigates the excess volatility in Bitcoin prices using an unbiased extreme value volatility estimator. We capture the time-varying nature of the …
terri michele jacobs georgiaWebNational Center for Biotechnology Information terri milliganWebMay 25, 2024 · Capital protected products are a special type of structured retail products that guarantee a minimum amount of payment at maturity. They were the earliest type of structured products and are very popular with risk averse investors, but nevertheless have become rare in the past years. Using a unique dataset of all structured products issued … brötje wbs 22i cenaWebAug 21, 2015 · Studying Binomial and Gaussian return dynamics in discrete time, we show how excess volatility can be traded to create growth. We test our results on real world … terrine mold substituteWebA new concept named volatility monotonous persistence duration (VMPD) dynamics is introduced into the research of energy markets, in an attempt to describe nonlinear fluctuation behaviors from a new perspective. The VMPD sequence unites the maximum fluctuation difference and the continuous variation length, which is regarded as a novel … terriloves lohjaWebMar 30, 2024 · Excess volatility appears to be inconsistent with a store of value but if the store of value is volatile only in the short run but relatively stable (or rising) in the long run, volatility may not be the major issue for Bitcoin as a store of value. ... [Google Scholar] Katsiampa P. Volatility estimation for bitcoin: a comparison of GARCH models ... terri sleevaWebFeb 28, 2024 · This article investigates the excess volatility in Bitcoin prices using an unbiased extreme value volatility estimator. We capture the time-varying nature of the excess volatility using bootstrap, multi-horizon, sub-sampling and rolling-window approaches. We observe that Bitcoin price changes are almost efficient. terri l austin books