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This textbook covers essential topics in quantitative finance, including stochastic calculus, portfolio optimization (static and dynamic), and risk-neutral pricing. Combining financial theory with real-world applications, the book presents a step-by-step guide to modelling financial data in continuous time using R and Python. The side-by-side presentation of the two software languages allows readers to grasp the similarities and differences between the two codes, while guiding them through models calibrated with actual market data that illustrate the quantitative characteristics of optimal portfolios.
Reinforced with pedagogical features including accompanying online datasets and numerical exercises to understand stochastic processes, this textbook will be a valuable resource for postgraduate students on corporate finance, quantitative finance, portfolio and investment management, risk management and actuarial courses, as well as finance professionals undertaking quantitative modelling.
About the author
Francesco Menoncin is Professor of Economic Policy in the Department of Economics and Management at the University of Brescia, Italy. He has extensive research and teaching experience across all areas of quantitative finance, including derivatives and risk management, equity and bonds, portfolio management, pension fund planning, stochastic modelling and more.
Summary
This textbook covers essential topics in quantitative finance, including stochastic calculus, portfolio optimization (static and dynamic), and risk-neutral pricing. Combining financial theory with real-world applications, the book presents a step-by-step guide to modelling financial data in continuous time using R and Python. The side-by-side presentation of the two software languages allows readers to grasp the similarities and differences between the two codes, while guiding them through models calibrated with actual market data that illustrate the quantitative characteristics of optimal portfolios.
Reinforced with pedagogical features including accompanying online datasets and numerical exercises to understand stochastic processes, this textbook will be a valuable resource for postgraduate students on corporate finance, quantitative finance, portfolio and investment management, risk management and actuarial courses, as well as finance professionals undertaking quantitative modelling.
