9798312129328 - optimization & numerical methods in quant finance: a practical guide to portfolio optimization, derivatives pricing, and risk management (technical topics for quant finance, band 3) von bisette, vincent; publishing, reactive; van der post, hayden (2 Ergebnisse)
Sprache: Englisch
Verlag: Independently published 2025
Serie: Technical Topics for Quant Finance, Buch 3 von 4. Buch 3 von 4 - Technical Topics for Quant Finance
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 19,30
EUR 13,80 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In.
Sprache: Englisch
Verlag: Independently Published Feb 2025 2025
Serie: Technical Topics for Quant Finance, Buch 3 von 4. Buch 3 von 4 - Technical Topics for Quant Finance
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 28,78
EUR 61,60 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingMaster Optimization & Numerical Methods for Smarter Financial Decision-MakingFinancial markets demand precision, and optimization & numerical methods are the backbone of portfolio management, option pricing, and risk assessment. From hedge funds to trading desks, mastering…these techniques allows quants, traders, and financial engineers to build faster, more efficient models that drive profitability and minimize risk.This comprehensive guide provides a step-by-step approach to applying optimization techniques and numerical algorithms to real-world financial problems, with a strong emphasis on practical implementation using Python.What You'll Learn: Linear & Nonlinear Optimization in Finance - Lagrange multipliers, convex optimization, and portfolio allocation strategiesNumerical Solutions for Option Pricing - Finite difference methods, binomial trees, and Monte Carlo simulationsGradient Descent & Machine Learning Applications - Optimizing financial models using stochastic gradient descent (SGD)Constrained Optimization for Risk Management - Value at Risk (VaR) and efficient frontier calculationsGlobal vs. Local Optimization - Genetic algorithms, simulated annealing, and evolutionary strategies in financeNumerical Linear Algebra for Quantitative Finance - Eigenvalue decomposition, PCA, and factor modelingPython Implementations & Real-World Case Studies - Hands-on coding with SciPy, NumPy, and PandasWho This Book is For: Traders & Portfolio Managers - Optimize asset allocation and risk-return profilesQuantitative Analysts & Financial Engineers - Build more efficient pricing and risk modelsStudents & Researchers in Finance & Data Science - Strengthen your foundation in applied mathematics and computationWith clear explanations, real-world case studies, and Python implementations, this book transforms optimization and numerical methods into powerful tools for financial decision-making.Enhance your financial models-get your copy today.
