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Python for Finance
A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Hands-On Data Science with Anaconda
Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda Key Features -Use Anaconda to find solutions for clustering, classification, and linear regression -Analyze your data efficiently with the most powerful data science stack -Use the Anaconda cloud to store, share, and discover projects and libraries Book Description Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in ...
Learning R and Python for Business School Students
This book provides a guide for business school students, individual investors, and business professionals to learn R and Python, two open-source programming languages. It is unique since it allows the reader to learn programming in an "R-assisted learning environment". The book provides 15 weeks' worth of teaching material for the reader.
Python for Finance
Learn and implement various Quantitative Finance concepts using the popular Python librariesAbout This Book* Understand the fundamentals of Python data structures and work with time-series data* Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib* A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to financeWho This Book Is ForThis book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.What You Will Learn* Become acquainted with Python in the fir...
Financial Modeling Using R
This is a programming book written by a finance professor. This book will be an ideal textbook for many quantitative finance courses, such as (next generation) financial modeling, portfolio theory, empirical research in finance, computational finance, and risk management. The book has three unique characteristics: (1) use free software; (2) combine programming with various finance theories, such as ratio analysis, CAPM, Fama-French 5-factor model, portfolio theory, options and futures, credit analysis, VaR (Value at Risk), and Monte Carlo Simulation; and (3) download and process publicly available financial and economic data from various sources, such as Yahoo! Finance, Google Finance, FRED (Federal Reserve Bank's Economic Data Library), SEC, and Prof. French's Data Library
Online Appendix for
This document is the Online Appendix to "Quality of PIN Estimates and the PIN-Return Relationship" by Yuxing Yan and Shaojun Zhang in Journal of Banking and Finance 43 (2014), pp 137-149. It includes two tables and four figures. The first table compares the two sets of quarterly PIN estimates that we obtain by using two methods to classify buyer-initiated and seller-initiated trades. One is the Lee and Ready (1991) algorithm with 5-second adjustment for delay in reported trade time. The other is the Ellis, Michaely and O'Hara (2000) algorithm without time adjustment. The second table compares the two sets of PIN estimates for actively and inactively traded stocks, separately. We divide stock...
Python for Finance
Learn and implement various Quantitative Finance concepts using the popular Python libraries About This Book Understand the fundamentals of Python data structures and work with time-series data Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance Who This Book Is For This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data. What You Will Learn Become acquainted with Python in the fir...
A New Paradigm for the MSF Programs
MSF stands for the Master of Science in Finance. In this paper, we propose a new scheme for the next-generation MSF programs. Here, the term of MSF is used to represent many similar programs, such as Master Degree of Financial Engineering, Quantitative Finance, Risk Management, Computational Finance and the like. Our approach could be summarized by three features: 1) replace C with Python or R plus SAS, 2) focus on data analytics, especially on financial data analytics, and 3) borrow a few courses from Business Analytics programs. In a sense, the new design could be viewed as the inter-join between the current MSF programs and Business Analytics programs. Alternatively, just remember three words: finance, programming and data.
Learning R and Python for Business School Students
This book provides a guide for business school students, individual investors, and business professionals to learn R and Python, two open-source programming languages. It is unique since it allows the reader to learn programming in an “R-assisted learning environment”. The book provides 15 weeks’ worth of teaching material for the reader.
Mastering pandas for Finance
If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.
