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Qualitative Research from Start to Finish, First Edition
This lively, practical text presents a fresh and comprehensive approach to doing qualitative research. The book offers a unique balance of theory and clear-cut choices for customizing every phase of a qualitative study. A scholarly mix of classic and contemporary studies from multiple disciplines provides compelling, field-based examples of the full range of qualitative approaches. Readers learn about adaptive ways of designing studies, collecting data, analyzing data, and reporting findings. Key aspects of the researcher's craft are addressed, such as fieldwork options, the five phases of data analysis (with and without using computer-based software), and how to incorporate the researcher's “declarative” and “reflective” selves into a final report. Ideal for graduate-level courses, the text includes:* Discussions of ethnography, grounded theory, phenomenology, feminist research, and other approaches.* Instructions for creating a study bank to get a new study started.* End-of-chapter exercises and a semester-long, field-based project.* Quick study boxes, research vignettes, sample studies, and a glossary.* Previews for sections within chapters, and chapter recaps.* Discussion of the place of qualitative research among other social science methods, including mixed methods research.
How I Became a Quant
Author: Richard R. Lindsey
language: en
Publisher: John Wiley & Sons
Release Date: 2011-01-11
Praise for How I Became a Quant "Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!" --Ira Kawaller, Kawaller & Co. and the Kawaller Fund "A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions." --David A. Krell, President and CEO, International Securities Exchange "How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis." --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management "Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk. How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.
Python for Finance
Author: Yves J. Hilpisch
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2018-12-05
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, author Yves Hilpisch also shows you 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.