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Books on the topic 'Optimal Hedging'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Vukina, Tomislaw. State-space forecasting approach to optimal intertemporal hedging. Kingston, R.I: University of Rhode Island, Dept. of Resource Economics, 1992.

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2

Vukina, Tomislaw. State-space forecasting approach to optimal intertemporal hedging. Kingston, R.I: University of Rhode Island, Dept. of Resource Economics, 1992.

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3

Deep, Akash. Optimal dynamic hedging using futures under a borrowing constraint. Basel, Switzerland: Bank for International Settlements, Monetary and Economic Dept., 2002.

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4

Harwood, Joy L. Year-specific estimation of optimal hedges for central Illinois soybean producers. Ithaca, N.Y: Dept. of Agricultural Economics, Cornell University Agricultural Experiment Station, New York State College of Agriculture and Life Sciences, Cornell University, 1987.

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5

Steil, Benn. Currency options and the optimal hedging of contingent foreign exchange exposure. Oxford: Nuffield College, 1992.

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6

Delaney, Brian. Dynamic hedging and time-varying optimal hedge ratio estimation with foreign currency futures. Dublin: University College Dublin, 1995.

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7

Qian, Ying. Optimal hedging strategy re-visited: Acknowledging the existence of non-stationary economic time series. [Washington, DC]: World Bank, International Economics Dept., International Trade Division, 1994.

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8

Thomas, Ted. A comprehensive approach to mortgage pipeline hedging: Using a variety of instruments for optimal hedge protection. Chicago (141 W. Jackson Blvd., Chicago 60604-2994): Chicago Board of Trade, 1999.

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9

Grant, Dwight. Optimal futures positions for corn and soybean growers facing price and yield risk. Washington, D.C: U.S. Dept. of Agriculture, Economic Research Service, 1989.

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10

Henry-Labordere, Pierre. Model-Free Hedging: A Martingale Optimal Transport Viewpoint. Taylor & Francis Group, 2017.

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11

Henry-Labordere, Pierre. Model-Free Hedging: A Martingale Optimal Transport Viewpoint. Taylor & Francis Group, 2017.

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12

Henry-Labordere, Pierre. Model-Free Hedging: A Martingale Optimal Transport Viewpoint. Taylor & Francis Group, 2017.

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13

Model-Free Hedging: A Martingale Optimal Transport Viewpoint. Taylor & Francis Group, 2017.

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14

Henry-Labordere, Pierre. Model-Free Hedging: A Martingale Optimal Transport Viewpoint. Taylor & Francis Group, 2017.

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15

Back, Kerry E. Continuous-Time Portfolio Choice and Pricing. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0014.

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The Euler equation is defined. The static approach can be used to derive an optimal portfolio in a complete market and when the investment opportunity set is constant. In the latter case, the optimal portfolio is proportional to the growth‐optimal portfolio and two‐fund separation holds. Dynamic programming and the Hamilton‐Jacobi‐Bellman equation are explained. An optimal portfolio consists of myopic and hedging demands. The envelope condition is explained. CRRA utility implies a CRRA value function. The CCAPM and ICAPM are derived.

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16

Back, Kerry E. Dynamic Portfolio Choice. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0009.

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The first‐order condition for optimal portfolio choice is called the Euler equation. Optimal consumption can be computed by a static approach in a dynamic complete market and by orthogonal projection for a quadratic utility investor. Dynamic programming and the Bellman equation are explained. The envelope condition and hedging demands are explained. Investors with CRRA utility have CRRA value functions. Whether the marginal value of wealth is higher for a CRRA investor in good states or in bad states depends on whether risk aversion is less than or greater than 1. With IID returns, the optimal portfolio for a CRRA investor is the same as the optimal portfolio in a single‐period model.

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17

Björk, Tomas. Arbitrage Theory in Continuous Time. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198851615.001.0001.

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The fourth edition of this textbook on pricing and hedging of financial derivatives, now also including dynamic equilibrium theory, continues to combine sound mathematical principles with economic applications. Concentrating on the probabilistic theory of continuous time arbitrage pricing of financial derivatives, including stochastic optimal control theory and optimal stopping theory, the book is designed for graduate students in economics and mathematics, and combines the necessary mathematical background with a solid economic focus. It includes a solved example for every new technique presented, contains numerous exercises, and suggests further reading in each chapter. All concepts and ideas are discussed, not only from a mathematics point of view, but the mathematical theory is also always supplemented with lots of intuitive economic arguments. In the substantially extended fourth edition Tomas Björk has added completely new chapters on incomplete markets, treating such topics as the Esscher transform, the minimal martingale measure, f-divergences, optimal investment theory for incomplete markets, and good deal bounds. There is also an entirely new part of the book presenting dynamic equilibrium theory. This includes several chapters on unit net supply endowments models, and the Cox–Ingersoll–Ross equilibrium factor model (including the CIR equilibrium interest rate model). Providing two full treatments of arbitrage theory—the classical delta hedging approach and the modern martingale approach—the book is written in such a way that these approaches can be studied independently of each other, thus providing the less mathematically oriented reader with a self-contained introduction to arbitrage theory and equilibrium theory, while at the same time allowing the more advanced student to see the full theory in action.

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18

Pfennig, Michael. Optimale Steuerung des Währungsrisikos mit derivativen Instrumenten. Gabler Verlag, 1998.

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