LibGuides: Finance Research: Software Guides/Cookbooks

Featured ebook collections

O'Reilly for Higher Education
1,700+ O'Reilly IT/computing books. Simultaneous access is limited to 30 UC users, so please click “Sign Out” when finished. ** To connect, select UCSD from the institutions, then login with your AD username/password. **
Springer Online monograph series
Includes feeds on particular academic and technical topics in the sciences and social sciences: business & economics, applied computing, math & statistics, computer science and engineering.
Taylor & Francis Collection
Includes the CRC Press and other e-book collections are primarily based in the sciences, and are great for getting up to speed quickly on a technology. Note: Not all CRC titles are licensed by UCSD.
Wiley E-Books (Wiley Online Library)
More than 9,000 (and counting) titles in the sciences, social sciences and humanities. Most from 2011 to date, with some selected titles from 2010 and earlier.

Books on using specific software

This section provides a sample of the types of materials you can find by browsing the subject links on the right.

Using Excel for Business and Financial Modelling: a practical guide, 3rd ed. by Danielle Stein Fairhurst
Call Number: Wiley e-book
ISBN: 9781119520382
Publication Date: 2019
A hands-on guide to using Excel in the business context that contains step-by-step instructions of how to solve common business problems using financial models. It includes downloadable Excel templates, a list of shortcuts and tons of tips. Learn to create financial models to help make business decisions while applying modelling best practice methodology, tools and techniques. This book focuses on the topics most relevant to finance professionals, and covers these features in detail, with real world examples.
Python for Finance: mastering data-driven finance, 2nd ed. by Yves Hilpisch
Call Number: Safari/O'Reilly e-book
ISBN: 9781492024330
Publication Date: 2018-12-31
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, learn how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
Hands-On Financial Modeling with Microsoft Excel 2019 by Shmuel Oluwa
Call Number: O'Reilly e-book
ISBN: 9781789534627
Publication Date: 2019
Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features.This book is a non-data professional’s guide to exploring Excel's financial functions and pivot tables. Learn to prepare various models for income and cash flow statements and balance sheets. Perform valuations and identify growth drivers using real-world case studies. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models; it assumes a working knowledge with Excel, however.
Data Science Using Python and R by Daniel T. Larose; Chantal D. Larose
Call Number: Wiley e-book
ISBN: 9781119526810
Publication Date: 2019
This book covers the two most widespread open-source platforms for data science: Python and R, so that readers may learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Written for the general reader with no previous analytics or programming experience, there are chapters dedicated to learning the basics and step-by-step instructions and walkthroughs for solving data science problems. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining.
R Cookbook, 2nd ed. by J. D. Long; Paul Teetor
Call Number: Safari/O'Reilly e-book
ISBN: 9781492040682
Publication Date: 2019-07-05
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.
Python for Data Mining Quick Syntax Reference by Valentina Porcu
Call Number: Springer e-book
ISBN: 9781484241127
Publication Date: 2019
Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This handy reference and tutorial covers topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis, including illustrative examples. The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.
Data Analysis with R: a comprehensive guide to manipulating, analyzing, and visualizing data in R, 2nd ed. by Fischetti, Anthony
Call Number: ProQuest e-book
ISBN: 9781788397339
Publication Date: 2018
Learn, by example, the fundamentals of data analysis as well as several intermediate to advanced methods and techniques ranging from classification and regression to Bayesian methods and MCMC, which can be put to immediate use

Previously featured items:

Learn Business Analytics in Six Steps Using SAS and R by Subhashini Tripathi Apply analytics to business problems using two very popular software tools, SAS and R. No matter your industry, this book will provide you with the knowledge and insights you and your business partners need to make better decisions faster.
Call Number: Springer ebook
ISBN: 9781484210024
Publication Date: 2016
Excel-Based Business Analysis by Ali Anari & James W. Kolari
Call Number: Springer e-book
ISBN: 9781461420507
Publication Date: 2012

Browsing Related Materials

Selected subjects for easy browsing:

TIPS: Don't see your favorite topic listed above? You can search your own topics and titles by using UC Library Search. For best results, sign in to UC Library Search using SSO and your @ucsd.edu email address. To limit to the most recent ebooks, choose the radio button that says "UC San Diego Library Catalog" for your search, then filter the results to online only. Changing the results order from "relevance" to "date: newest first" will show the most recent additions to the ebook collection.

Featured Items

Getting Started with Enterprise Blockchain by Michael Bradley et al.
Call Number: Safari/O'Reilly e-book
ISBN: 9781492052708
Publication Date: 2019
This ebook explains how developers can establish a blockchain network to handle business-to-business transactions while maintaining privacy and confidentiality. Content from members of IBM’s global blockchain team.

O'Reilly for Higher Education
O’Reilly for Higher Education includes more than 38K computer science, engineering, business book titles from 200+ publishers. Plus 30K+ hours of video, proven learning paths, case studies, expert playlists, audio books, and more. Includes pre-publication titles published by O'Reilly.
Access with Single Sign On after choosing University of California San Diego from the list of institutions.

Note: Access is limited to current students, staff, and faculty at the University of California campuses. No community use.
Titles are html only.
Replaces the Safari Tech Books Online collection.

Here are some specific titles of interest from the O'Reilly ebooks:

Using R for finance:

Learning Quantitative Finance with R (2017)
Beginning R (2012)
Apress series on Advanced Statistical Programming for Data Science, Analysis and Finance

Using for Python for finance:

Video

Finance Research: Software Guides/Cookbooks

Books on data analysis theory & techniques for business & economics

Python for Finance, 2nd ed.

Python Workbook: an Introduction with Exercises & Solution

Data Science Using Python and R

Introduction to Business Analytics Using Simulation

Essentials of Business Analytics: an Introduction to the Methodology and its Applications

Data Infrastructure for Next-Gen Finance

Fluent Python

Quantitative Investment Analysis

Business Risk and Simulation Modeling in Practice

Analytics in a Big Data World

Derivatives Analytics with Python

Featured ebook collections

Books on using specific software

Previously featured items:

Browsing Related Materials

Featured Items