1,355,886 research outputs found
HEDGING USING SIMULATION: A LEAST SQUARES APPROACH.
No full textThis paper presents a new and flexible computational approach to derivative hedging. It is based on the use of least squares regression in order to compute the hedging portfolio. This nonparametric methodology can be readily applied to any derivative contract written on a single underlying risky asset in a complete market with continuous Markov price paths. We illustrate this technique computing sensitivities on plain vanilla and exotic options with both European and American exercise style. The achieved numerical accuracy is always comparable with the best simulation and semianalytic techniques presented in the literature. © 2004 Elsevier B.V. All rights reserved
Mauro Tebaldi, Il Presidente della Repubblica, Bologna, Il Mulino, 2005, pp. 343.
No full textThe author offers a review of the book by M. Tebaldi concerning the President of the Repubblic in the Italian constitutional system
Effect On Pavement Performance of a Sub Base Layer Composed By Natural Aggregates And Rap
No full textReclaimed Asphalt Pavement (RAP) recycling in pavement engineering can be actually carried out by means of hot recycling and cold recycling. An additional option arise from mixing with natural aggregates to build the sub-base layer. This paper shows the first results of a research activity undertaken on a test track specifically constructed with the aim to analyze the effect on pavement performance of a sub-base layer mixture with 50% of natural aggregates and 50% of RAP. The investigation is based on LWD and FWD analysis, comparing results with those obtained on the subsequent section of the test track made by only natural aggregates
Bryant Faculty Spotlight, Episode 10: Edi Tebaldi
No full textThis podcast is part of the Bryant Faculty Spotlight series. In this episode, Dr. Edi Tebaldi, a professor in the Economics department, discusses his research on economic growth and innovation.https://digitalcommons.bryant.edu/faculty-spotlight-podcast/1009/thumbnail.jp
Supporting data for Tebaldi et al. 2021 - Nature Climate Change
No full textThis is the dataset underpinning the paper "Extreme Sea Levels at Different Global Warming Levels" accepted in Nature Climate Change in 2021. Information about the paper as well as the supporting code used to process and analyze the data can be found at: https://github.com/DOE-ICoM/tebaldi-etal_2021_natclimchange.This research was supported by the U.S. Department of Energy, Office of Science, as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling Program. Pacific Northwest National Laboratory is a multi-program national laboratory operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830
Branching processes and evolution at the ends of a food chain
No full textIn a critically self-organized model of punctuated equilibrium, boundaries determine peculiar scaling of the size distribution of evolutionary avalanches. This is derived by an inhomogeneous generalization of standard branching processes, extending previous mean field descriptions and yielding v = 1/2 together with T’ = 7/4, as distribution exponent of avalanches starting from species at the ends of a food chain. For the nearest neighbor chain one obtains numerically T’ = 1.25 ± 0.01, and Tfirst’ = 1.35 ± 0.01 for the first return times of activity, again distinct from bulk exponents© 1996 The American Physical Society
The power of the President: a quantitative narrative analysis of the Diary of an Italian head of state (2006–2013)
No full textMany authors agree that the President of the Italian Republic is the head of state with the widest powers among parliamentary governments in Europe. Although several studies have sought to explain Why the President’s power may increase or decrease, a quantitative measurement of the phenomenon—able to answer questions also about the Who (the actors), How (the modalities) and How much (the consistency) of the phenomenon itself—has seldom been carried out by scholars. This paper seeks to answer these unanswered substantive questions by measuring the potential power of the Italian head of state in a crucial case—the first Presidency of Giorgio Napolitano (2006–2013)—by means of a quantitative narrative analysis (QNA) and a social network analysis of his Diary. This is done in a semi-automated way by using natural language processing (NLP) techniques, including regular expressions and named-entity recognition. As regards the methodological contribution of the paper, its aim is to demonstrate that QNA with NLP tools for semi-automated analysis of textual data can be considered an effective and reliable methodology for the empirical investigation of potential power, enabling a more widespread application of this technique in the quantitative analysis of topics related to the power approach—that some scholars consider otherwise obsolete—also at the comparative level
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