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Stochastic Differential Equations and Stochastic Optimal Control for Economists: Learning by Exercising

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These notes originate from my own efforts to learn and use Ito-calculus to solve stochastic differential equations and stochastic optimization problems. Although the material contains theory and, at least, sketches of proofs, most of the material consists of exercises in terms of problem solving. The problems are borrowed from textbooks that I have come across during my own attempts to become an amateur mathematician. However, my Professors Björk, Nyström and Öksendal have done extremely work to help me. Tomas Björk and Bernt Öksendal have made my help with the books Arbitrage Theory in Continuous Time and Stochastic Differential Equations, and they are excellent. Kaj Nyström is a fantastic mathematician and teacher, and he has been one of the very best to help me with the booaks from Björk and Öksendal.

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  • Löfgren, Karl-Gustaf, 2017. "Stochastic Differential Equations and Stochastic Optimal Control for Economists: Learning by Exercising," Umeå Economic Studies 949, Umeå University, Department of Economics.
    • Handle: RePEc:hhs:umnees:0949
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    References listed on IDEAS

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    1. Thomas Aronsson & Karl-Gustaf Löfgren & Kenneth Backlund, 2004. "Welfare Measurement in Imperfect Markets," Books, Edward Elgar Publishing, number 2494.
    2. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    3. Martin L. Weitzman, 1976. "On the Welfare Significance of National Product in a Dynamic Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 90(1), pages 156-162.
    4. Robert C. Merton, 1975. "An Asymptotic Theory of Growth Under Uncertainty," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(3), pages 375-393.
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    More about this item

    Keywords

    Stochastic differential equations; stochastic optimal control and finance;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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