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Record Nr. |
UNINA9910897983503321 |
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Autore |
Rivas Moreno Juan José |
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Titolo |
The Capital Market of Manila and the Pacific Trade, 1668-1838 : Institutions and Trade during the First Globalization / / by Juan José Rivas Moreno |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Palgrave Macmillan, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (303 pages) |
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Collana |
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Palgrave Studies in Economic History, , 2662-6500 |
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Disciplina |
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Soggetti |
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Economic history |
Finance |
History |
Economics |
International trade |
Economic History |
Financial History |
Political Economy and Economic Systems |
International Trade |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter I: Introduction -- Chapter II - The Manila Trade -- Chapter III - The Capital Markets of the Manila Trade -- Chapter IV - The Business Model of the one-Galleon System -- Chapter V - An Alternative model of Trade Finance -- Chapter VI - The Political Economy of the Manila trade -- Chapter VII - Conclusion. |
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Sommario/riassunto |
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Economic history has always emphasized the importance of long-distance trade in the emergence of modern financial markets, yet almost nothing is known about the Manila trade. This book offers the first reconstruction of the capital market of Manila using new archival |
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sources that have never been used in the economic history of Pacific trade. The book explains how trade between Asia and Spanish America across the Pacific, which lasted for 250 years (1571 - 1815) was financed from the city of Manila.The book analyses the political economy and institutional structures of the Manila capital market in the context of the global silver trade, as well as addressing key similarities and differences with European trade routes and differing approaches to colonialism and commerce in Asian waters. It traces how the Manila capital market emerged in a bottom-up process with a redistributive aspect that tied the interests of citizens with the fortunes of trade, using institutions familiar to the public like legacy funds, brotherhoods and lay religious orders to pool liquidity, originate working capital, and internalise the risk of loss at sea. It challenges the notion that there is a normative model for the development of capital markets and introduces an industrial organisation analysis to the broader structure of Early Modern trade in the Spanish Empire. Sitting at the intersection of economic and financial history, global history, imperial history and political economy, this book will be a cutting-edge and valuable resource for a broad range of scholars. Juan José Rivas Moreno is a historian of early modern finance, specialising in the financing of the Pacific trade. He obtained his PhD in Economic History from London School of Economics in 2023 with a thesis on the capital market of Manila which received the Coleman Prize 2024. Juan José was the recipient of a Newberry Library short-term fellowship and held an Economic History Society Fellowship in 2023-2024. Currently he is a Max Weber fellow at the European University Institute in Florence. |
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2. |
Record Nr. |
UNINA9910973016703321 |
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Autore |
Cacuci Dan Gabriel |
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Titolo |
The Second-Order Adjoint Sensitivity Analysis Methodology / / by Dan Gabriel Cacuci |
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Pubbl/distr/stampa |
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Boca Raton, FL : , : Chapman and Hall/CRC, , 2018 |
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ISBN |
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1-351-64658-3 |
1-315-12027-5 |
1-4987-2649-6 |
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Edizione |
[First edition.] |
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Descrizione fisica |
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1 online resource (327 pages) |
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Collana |
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Advances in Applied Mathematics |
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Disciplina |
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Soggetti |
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Sensitivity theory (Mathematics) |
Large scale systems |
Nonlinear systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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MOTIVATION FOR COMPUTING FIRST- AND SECOND-ORDER SENSITIVITIES OF SYSTEM RESPONSES TO THE SYSTEMS PARAMETERS -- The Fundamental Role of Response Sensitivities for Uncertainty Quantification -- The Fundamental Role of Response Sensitivities for Predictive Modeling -- Advantages and Disadvantages of Statistical and Deterministic Methods for Computing Response Sensitivities -- ILLUSTRATIVE APPLICATION OF THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) TO A LINEAR EVOLUTION PROBLEM -- Exact Computation of the 1st-Order Response Sensitivities -- Exact Computation of the 2nd-Order Response Sensitivities -- Computing the 2nd-Order Response Sensitivities Corresponding to the 1st-Order Sensitivities -- Discussion of the Essential Features of the 2nd-ASAM -- Illustrative Use of Response Sensitivities for Predictive Modeling -- THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) FOR LINEAR SYSTEMS -- Mathematical Modeling of a General Linear System -- The 1st-Level Adjoint Sensitivity System (1st-LASS) for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems -- The 2nd-Level Adjoint Sensitivity System (2nd-LASS) |
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for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems -- APPLICATION OF THE 2nd-ASAM TO A LINEAR HEAT CONDUCTION AND CONVECTION BENCHMARK PROBLEM -- Heat Transport Benchmark Problem: Mathematical Modeling -- Computation of First-Order Sensitivities Using the 2nd-ASAM -- Computation of first-order sensitivities of the heated rod temperature -- Computation of first-order sensitivities of the coolant temperature -- Verification of the "ANSYS/FLUENT Adjoint Solver" -- Applying the 2nd-ASAM to Compute the Second-Order Sensitivities and Uncertainties for the Heat Transport Benchmark Problem -- APPLICATION OF THE 2nd-ASAM TO A LINEAR PARTICLE DIFFUSION PROBLEM -- Paradigm Diffusion Problem Description -- Applying the 2nd-ASAM to Compute the First-Order Response Sensitivities to Model Parameters -- Applying the 2nd-ASAM to Compute the Second-Order Response Sensitivities to Model Parameters -- Role of Second-Order Response Sensitivities for Quantifying Non-Gaussian Features of the Response Uncertainty Distribution -- Illustrative Application of First-Order Response Sensitivities for Predictive Modeling -- APPLICATION OF THE 2nd-ASAM FOR COMPUTING SENSITIVITIES OF DETECTOR RESPONSES TO UNCOLLIDED RADIATION TRANSPORT -- The Ray-Tracing Form of the Forward and Adjoint Boltzmann Transport Equation -- Application of the 2nd-ASAM to Compute the First-Order Response Sensitivities to Variations in Model Parameters -- Application of the 2nd-ASAM to Compute the Second-Order Response Sensitivities to Variations in Model Parameters -- THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) FOR NONLINEAR SYSTEMS -- Mathematical Modeling of a General Nonlinear System -- The 1st-Level Adjoint Sensitivity System (1st-LASS) for Computing Exactly and Efficiently the 1st-Order Sensitivities of Scalar-Valued Responses -- The 2nd-Level Adjoint Sensitivity System (2nd-LASS) for Computing Exactly and Efficiently the 2nd-Order Sensitivities of Scalar-Valued Responses for Nonlinear Systems -- APPLICATION OF THE 2nd-ASAM TO A NONLINEAR HEAT CONDUCTION PROBLEM -- Mathematical Modeling of Heated Cylindrical Test Section -- Application of the 2nd-ASAM for Computing the 1st-Order Sensitivities -- Application of the 2nd-ASAM for Computing the 2nd-Order Sensitivities. |
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Sommario/riassunto |
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The Second-Order Adjoint Sensitivity Analysis Methodology generalizes the First-Order Theory presented in the author’s previous books published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions. The book has many illustrative examples that will help readers understand the complexity of the subject and will enable them to apply this methodology to problems in their own fields. Highlights: • Covers a wide range of needs, from graduate students to advanced researchers • Provides a text positioned to be the primary reference for high-order sensitivity and uncertainty analysis • Applies to all fields involving numerical modeling, optimization, quantification of sensitivities in direct and inverse problems in the presence of uncertainties. About the Author: Dan Gabriel Cacuci is a South Carolina SmartState Endowed Chair Professor and the Director of the Center for Nuclear Science and Energy, Department of Mechanical Engineering at the University of South Carolina. He has a Ph.D. in Applied Physics, Mechanical and Nuclear Engineering from Columbia University. He is also the recipient of many awards including four honorary doctorates, the Ernest Orlando Lawrence Memorial award from the U.S. Dept. of Energy and the Arthur Holly Compton, Eugene P. Wigner and the Glenn Seaborg Awards from |
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the American Nuclear Society. |
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