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An Elementary Introduction to Mathematical Finance

Author

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  • Ross,Sheldon M.

Abstract

This textbook on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon M. Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula, and other topics such as utility functions, optimal portfolio selections, and the capital assets pricing model. Among the many new features of this third edition are new chapters on Brownian motion and geometric Brownian motion, stochastic order relations and stochastic dynamic programming, along with expanded sets of exercises and references for all the chapters.

Suggested Citation

  • Ross,Sheldon M., 2011. "An Elementary Introduction to Mathematical Finance," Cambridge Books, Cambridge University Press, number 9780521192538, January.
    • Handle: RePEc:cup:cbooks:9780521192538
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    Citations

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    Cited by:

    1. Rajeshwari Majumdar & Phanuel Mariano & Lowen Peng & Anthony Sisti, 2018. "A derivation of the Black-Scholes option pricing model using a central limit theorem argument," Papers 1804.03290, arXiv.org, revised Aug 2018.
    2. Tiago P. Abud & Andre A. Augusto & Marcio Z. Fortes & Renan S. Maciel & Bruno S. M. C. Borba, 2022. "State of the Art Monte Carlo Method Applied to Power System Analysis with Distributed Generation," Energies, MDPI, vol. 16(1), pages 1-24, December.
    3. Steven Andrew Culpepper & James Joseph Balamuta, 2017. "A Hierarchical Model for Accuracy and Choice on Standardized Tests," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 820-845, September.
    4. Zhang, Huiming & Liu, Yunxiao & Li, Bo, 2014. "Notes on discrete compound Poisson model with applications to risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 325-336.
    5. Ahmadian, D. & Farkhondeh Rouz, O. & Ivaz, K. & Safdari-Vaighani, A., 2020. "Robust numerical algorithm to the European option with illiquid markets," Applied Mathematics and Computation, Elsevier, vol. 366(C).
    6. Roberto Mota Navarro & Francois Leyvraz & Hern'an Larralde, 2023. "Dynamical properties of volume at the spread in the Bitcoin/USD market," Papers 2304.01907, arXiv.org, revised May 2023.
    7. Zheqing Zhu & Jian-guo Liu & Lei Li, 2017. "A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction," Papers 1709.03611, arXiv.org.
    8. Debnath, Biswajit & El-Hassani, Rihab & Chattopadhyay, Amit K. & Kumar, T. Krishna & Ghosh, Sadhan K. & Baidya, Rahul, 2022. "Time evolution of a Supply Chain Network: Kinetic modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    9. Liu, Chang & Chang, Chuo, 2021. "Combination of transition probability distribution and stable Lorentz distribution in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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