Titel: Practical Quantitative Finance with ASP.NET Core and Angular: Building Ultra-Modern, Responsive Single-Page Web Applications for Quantitative Finance
Verlag: UniCAD Publishing
Erscheinungsjahr: 2019
Sprache: Englisch
ISBN-10: 0979372569
ISBN-13: 9780979372568
Einband: Softcover
Zustand: New

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Inhaltsangabe

This book provides comprehensive details of developing ultra-modern, responsive single-page applications (SPA) for quantitative finance using ASP.NET Core and Angular. It pays special attention to create distributed web SPA applications and reusable libraries that can be directly used to solve real-world problems in quantitative finance. The book contains:

Overview of ASP.NET Core and Angular, which is necessary to create SPA for quantitative finance.

Step-by-step approaches to create a variety of Angular compatible real-time stock charts and technical indicators using ECharts and TA-Lib.

Introduction to access market data from online data sources using .NET Web API and Angular service, including EOD, intraday, real-time stock quotes, interest rates.

Detailed procedures to price equity options and fixed-income instruments using QuantLib, including European/American/Barrier/Bermudan options, bonds, CDS, as well as related topics such as cash flows, term structures, yield curves, discount factors, and zero-coupon bonds.

Detailed explanation to linear analysis and machine learning in finance, which covers linear regression, PCA, KNN, SVM, and neural networks.

In-depth descriptions of trading strategy development and backtesting for crossover and z-score based trading signals.

Rese�a del editor

Overview of ASP.NET Core and Angular, which is necessary to create SPA for quantitative finance.

Step-by-step approaches to create a variety of Angular compatible real-time stock charts and technical indicators using ECharts and TA-Lib.

Introduction to access market data from online data sources using .NET Web API and Angular service, including EOD, intraday, real-time stock quotes, interest rates.

Detailed explanation to linear analysis and machine learning in finance, which covers linear regression, PCA, KNN, SVM, and neural networks.

In-depth descriptions of trading strategy development and backtesting for crossover and z-score based trading signals.

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