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Overview: This book is about dynamic programming and its applications in economics, finance, and adjacent fields like operations research. It brings together recent innovations in the theory of dynamic programming and also provides related applications and computer code. Chapters 1–3 provide motivation and background material on solving fixed point problems and computing lifetime valuations. Chapters 4 and 5 cover optimal stopping and Markov decision processes respectively. Chapter 6 extends the Markov decision framework to settings where discount rates vary over time. Chapter 7 treats recursive preferences. The main theoretical results on dynamic programming from Chapters 4–6 are special cases of the general results in Chapters 8–9. A brief discussion of continuous time models can be found in Chapter 10. One feature of the text is that computer code is a first-class citizen. The code embedded in the textbook is written in Julia and can be found at GitHub. We chose Julia because it is open source and because Julia allows us to write computer code that is as close as possible to the relevant mathematical equations. Julia code in the text is written to maximize clarity rather than speed. We have also written matching Python code, which can be found in the same repository.
Genre: Non-Fiction > Tech & Devices
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