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Portfolio Management in Continuous Time

Numerical Applications in R and Python

Medium: Buch
ISBN: 978-3-031-99909-3
Verlag: Springer International Publishing AG
Erscheinungstermin: 28.11.2026
vorbestellbar, Erscheinungstermin ca. November 2026

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.


Produkteigenschaften


  • Artikelnummer: 9783031999093
  • Medium: Buch
  • ISBN: 978-3-031-99909-3
  • Verlag: Springer International Publishing AG
  • Erscheinungstermin: 28.11.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Produktform: Kartoniert
  • Seiten: 153
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Chapter 1: Introduction.- Chapter 2: Stochastic processes.- Chapter 3: Loading External Data.- Chapter 4: Simulation of Stochastic Processes.- Chapter 5: Estimation of Stochastic Process Parameters and Future Prediction.- Chapter 6: The Poisson Process.- Chapter7: Mean-Reverting Processes.- Chapter 8: Modeling a Diffusion Financial Market.- Chapter 9: The (Instantaneously) Optimal Portfolio.- Chapter 10: Asset Pricing.- Chapter 11: The Dynamically Optimal Portfolio.