Portfolio Management in Continuous Time
Numerical Applications in R and Python
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Beschreibung
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.
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.
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.
Presents side-by-side explanations in R and Python to reinforce learning Introduces foundational stochastic processes and applies them to financial models and portfolio construction Combines quantitative finance theory with real-world applications and dual-language coding
Autor*in
Francesco Menoncin
Themen in »Portfolio Management in Continuous Time«
Stochastic calculus Stochastic processes in finance Optimal portfolio Dynamic portfolio theory R Python Modelling in continuous time Modelling financial data Mathematical finance Quantitative finance textbook Portfolio management textbook Asset pricing Financial models Geometric Brownian motions Mean-reverting processes