Analyzing financial data and implementing financial models using R

By: Ang, Clifford S Material type: Text

TextPublication details: Switzerland Springer 2020 Description: xvi, 465 pISBN: 9783030641542Subject(s): R (Computer program language) | Finance--Mathematical models | Mathematical statistics | Finance--Data processing | Decision making--Computer programs | Decision making--Mathematical models | Industrial management--Statistical methods--Computer programsDDC classification: 332 Summary: About this book This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

List(s) this item appears in: Finance & Accounting | HR & OB

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Finance & Accounting	332 ANG (Browse shelf(Opens below))	1	Available		002760

About this book
This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

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