Summaries for Quantitative Finance

Numerical Analysis

NIST Digital Library of Mathematical Functions. Companion to NIST Handbook of Mathematical Functions.

John Burkardt's advice on choosing numerical integration routines from QUADPACK.

David Goldberg: What Every Computer Scientist Should Know About Floating-Point Arithmetic.
William H. Press, Brian P. Flannery, Saul A. Teukolsky, and William T. Vetterling. Numerical Recipes in C: The Art of Scientific Computing, 2nd edition. numerical.recipes.

Statistics, Econometrics, and Machine Learning

NIST/SEMATECH e-Handbook of Statistical Methods. This handbook is to help scientists and engineers incorporate statistical methods in their work efficiently.
StatLib--Applied Statistics algorithms. 300+ statistical algorithms published by The Royal Statistics Society.
The Big Picture
- 陈希孺：《数理统计学简史》。长沙：湖南教育出版社，2002。
- 陈希孺：《统计学概貌》。科学文献技术出版社，1989。
- Larry Wasserman. All of Statistics.
- Peter Kennedy. A Guide to Econometrics. Wiley-Blackwell; 6th edition (February 19, 2008). Amazon.
- Bradley Efron and Trevor Hastie. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press (July 21, 2016).
- "I am not an econometrician", "What Are The Differences Between Econometrics, Statistics, and Machine Learning?", "Econometrics versus Statistics".
Boot Camp
- Matthew Stephens. Five Minutes Stats.
- Quick-R: Basic Statistics, Advanced Statistics.
- Simon Wood. Core Statistics.
- Allen B. Downey. Think Stats: Probability and Statistics for Programmers. O'Reilly Media; 1 edition (July 25, 2011). Amazon.
- Allen B. Downey. Think Bayes: Bayesian Statistics Made Simple. O'Reilly Media: 1 edition (October 8, 2013). Amazon.
- Python 'statsmodels' package: User Guide, Examples, Tutorials by Mode.com, Official Documentation, StatsModels at devdocs.io.
- Google: Machine Learning Crash Course.
Iteration 1:
- Dmitry Panchenko. MIT Open Course 18.443: Statistics for Applications. MIT OCW, Fall 2003. Course website.
- Roberto Pedace. Econometrics for Dummies. For Dummies (June 24, 2013). Amazon.
- Trevor Hastie and Rob Tibshirani: In-depth Introduction to Machine Learning in 15 Hours of Expert Videos.
Iteration 2:
- 陈家鼎、孙山泽、李东风、刘力平编著：《数理统计学讲义（第2版）》。北京：高等教育出版社，2003。
- 何书元编著：《应用时间序列分析》。北京：北京大学出版社，2003。
- David Ruppert. Statistics and Data Analysis for Financial Engineering. Springer (November 17, 2010). Amazon.
- Ruey S. Tsay. Analysis of Financial Time Series. Wiley; 3rd edition (August 30, 2010). Amazon.
- Andriy Burkov. The Hundred-Page Machine Learning Book. 2019-07-05. LeanPub.
Iteration 3:
- Fumio Hayashi. Econometrics. Princeton University Press (December 15, 2000). Amazon.
- Anna Mikusheva. MIT Open Course 14.384: Time Series Analysis. MIT OCW, Fall 2013. Course website.
- Aurélien Géron. Hands-On Machine Learning with Scikit-Learn and TensorFlow. O'Reilly Media (April 18, 2017). Amazon.
Additional: Generalized Additive Models
- Kim Larsen. GAM: The Predictive Modeling Silver Bullet (July 30, 2015).
- Magne Aldrim. Generalized additive models in R (with examples, October, 2012).
- Trevor Hastie. Package 'gam' (July 20, 2018).
- Simon Wood. Website at University of Bristol (GAM and more).
Additional: Regression Diagnostics
- 韦博成、鲁国斌、史建清：《统计诊断引论》。南京：东南大学出版社，1991。
- John Fox:
  1. Regression Diagnostics, presentation slides, Brazil, November 2009.
  2. Regression Diagnostics: An Introduction,. SAGE Publications, Inc; 2 edition (December 9, 2019)
  3. Applied Regression Analysis and Generalized Linear Models. SAGE Publications, Inc; Third edition (April 15, 2015).
  4. An R Companion to Applied Regression. SAGE Publications, Inc; 3 edition (October 16, 2018).
- Sanford Weisberg:
  1. Applied Linear Regression. Wiley; 4 edition (December 23, 2013).
  2. Statistics 8311: Linear Models (Fall 2006).
- Jonathan Taylor. Stats203: Introduction to Regression Models and Analysis of Variance (diagnostics, model selection).
- Michael Kutner, Christopher Nachtsheim and John Neter. Applied Linear Regression Models; McGraw-Hill; 4th edition (2004). Amazon.
- Quick-R: Regression Diagnostics with package 'car'.
- Python 'statsmodels' package: Regression Diagnostics and Specification Tests, example.
- Miscellaneous: Q-Q Plots Explained. Model Selection Techniques: An Overview. A Gentle Introduction to Model Selection for Machine Learning. Probabilistic Model Selection with AIC, BIC, and MDL.
Additional: Econometrics
- Colin Cameron. Ph.D. Econometrics Sequence at UC Davis: Econ 240A. Econometrics Methods I. Econ 240D. Cross Section Econometrics.
- Chris Brooks. Introductory Econometrics for Finance, video lectures, publisher's resources site.
- Robert H. Shumway and David S. Stoffer. Time Series Analysis and Its Applications with R Examples. Springer; 4th ed. (April 19, 2017). Amazon.
- NBER Method Lectures (Summer 2008).
Software Packages
- R packages for outlier detection: "CausalImpact", "extremevalues", "outliers", "OutlierDetection", "OutlierO3", the Local Outlier Factor algorithm.
- Robust statistics: Rand Wilcox, UCLA IDRE.

Optimization

Dimitris Bertsimas. MIT Open Course 15.093J / 6.255J: Optimization Methods. MIT OCW, Fall 2009. Website.
Package scipy.optimize: API reference, tutorial.
Package CVXOPT.
Package CVXPY.

Data Science

Jeroen Janssens: Data Science at the Command Line.
Machine Learning
- Yaser Abu-Mostafa. Learning From Data: Lectures recorded at CalTech.
- Kevin Murphy & Francis Bach. Machine Learning: A Probabilistic Perspective. The MIT Press; 1 edition (August 24, 2012). Amazon.
- Christopher Bishop. Pattern Recognition and Machine Learning. Springer (April 6, 2011). Amazon.
- Coursera. Machine Learning by Andrew Ng.
- Andreas Mueller and Sarah Guido. Introduction to Machine Learning with Python. O'Reilly Media; 1 edition (October 21, 2016). Amazon.
- Sebastian Raschka & Vahid Mirjalili. Python Machine Learning. Packt Publishing; 2nd edition (September 20, 2017). Amazon.
- Scikit-Learn.
Visualization

Programming Learning Paths

General Resources

Code Sandbox: https://codesandbox.io/
DevDocs API Documentation: https://devdocs.io/
Free Code Camp: https://www.freecodecamp.org/
StarUML 3: http://staruml.io/

Full Stack Web Development

The Big Picture of Web Development: Web Development Roadmaps and Mindmaps.
- Front-End Roadmap, Back-End Roadmap
Full Stack Web Development: HTTP/CSS, browser (JavaScript, jQuery, Angular), server (PHP, ASP, Python, Node), database (SQL, MongoDB).
- What is Full Stack
- What is Full Stack JS
The Big Picture of Database Technology: What is NoSQL? Databases on AWS, Amazon DynamoDB.
MDN: Learn web development.
Udemy: The Complete 2019 Web Development Bootcamp by Angela Yu, with the App Brewery Web Development Course Resource List.
Client Side:
- HTML (W3Schools, MDN.): create content.
- CSS / W3.CSS / MDN CSS reference: describe content style.
- Bootstrap 4: responsive front-end framework with HTML and CSS based design templates. Balsamiq Cloud, getbootstrap, bootsnipp.
- JavaScript / W3.JS: programming language of HTML and the browser. Style guide.
- jQuery: JavaScript library to simplify JavaScript programming; after JavaScript version 5 (2009), most utilities can be solved easily by standard JavaScript.
- React: JavaScript library for building user interfaces and single page applications. Tutorial: Intro to React. Airbnb React/JSX Style Guide.
- AngularJS: HTML extension.
- HTML DOM / XML DOM: Document Object Model and programming interface of a document
- AJAX: a web development technique that uses a combination of XMLHttpRequest (data request) and JavaScript / HTML DOM (data consumption)
- JSON, XML: data exchange and data storage
Programming: Python (to work with JSON, MySQL, MongoDB), C# (to work with ASP.NET).
Server Side:
- Node.js: a JavaScript library that executes JavaScript code outside of a browser
- Express.js: a minimal and flexible Node.js web application framework
- EJS: a simple templating language that lets you generate HTML markup with plain JavaScript
- PHP, ASP: server side scripting languages
- SQL, MySQL Connector/Python: tutorials for relational database
- MongoDB: tutorials for nonrelational database
- Mongoose: an Object Data Modeling (ODM) library for MongoDB and Node.js
- REST: an architectural style for distributed hypermedia systems
- Authentication & Security: haveibeenpwned, bcrypt, Passport.js, OAuth 2.0.

Other References:
- Artur Ejsmont. Web Scalability for Startup Engineers. McGraw-Hill Education; 1st edition (June 23, 2015). Amazon.
- Mikito Takada. Distributed Systems for Fun and Profit.
- Martin Kleppmann. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. March 16, 2017). Amazon.
- Oracle. Database Reference.
- TechOnTheNet. Tutorials on SQL, Oracle/PLSQL, SQL Server, MySQL, MariaDB, PostgreSQL, SQLite.
- SQL Alchemy.

Python

Get Started
- IDE: PyDev, Spyder, PyCharm, Visual Studio.
- Anaconda. 1) Conda User Guide. 2) Getting Started with Anaconda Navigator.
- Style Guide: PEP8 -- Style Guide for Python Code, Google Python Style Guide, cheat sheet.
- TutorialsPoint.com. Python 3 Tutorial.
- Python.org: The Python Tutorial, The Python Standard Library, Python HOWTOs.
- GeeksforGeeks: Python Programming Language.
- Jake VanderPlas. A Whirlwind Tour of Python. O'Reilly Media; 1st edition (August, 2016).
- Jake VanderPlas. Python Data Science Handbook. O'Reilly Media; 1 edition (December 10, 2016). Amazon.
- Wes McKinney. Python for Data Analysis. O'Reilly Media; 2nd edition (October 20, 2017). Amazon.
- Theodore Petrou: Minimally Sufficient Pandas, Minimally Sufficient Pandas Cheat Sheet.
- Theodore Petrou. Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization. (October 23, 2017), Amazon.
- Magnus L. Hetland. Beginning Python: From Novice to Professional. Apress; 3rd ed. (March 10, 2017). Amazon.
- Kenneth Reitz & Tanya Schlusser. The Hitchhiker's Guide to Python: Best Practices for Development. O'Reilly Media; (September 18, 2016). Amazon.
- Python common knowledge: The import system, The Definite Guide to Python import Statements.
- Pandas common knowledge: A look inside pandas design and development, SettingwithCopyWarning.
- Pandas Cheat Sheet. Data Wrangling with Pandas, Python for Data Science Pandas Basics, Kaggle Pandas Cheatsheet.

Intermediate
- David Beazley and Brian K. Jones. Python Cookbook. O'Reilly Media; 3rd edition (June 1, 2013). Amazon
- Luciano Ramalho. Fluent Python. O'Reilly Media; 1 edition (August 20, 2015). Amazon.
- Brett Slatkin. Effective Python: 59 Specific Ways to Write Better Python. Addison-Wesley Professional; 1 edition (March 8, 2015). Amazon.
- Paul Deitel. Python Fundamentals LiveLessons. Prentice Hall (August, 2019).
- Julien Danjou. Serious Python: Black-Belt Advice on Deployment, Scalability, Testing, and More. (2019). Amazon.
- Matt Makai. Full Stack Python.
- O'Reilly's Python resource.
For Python Developers
- Python.org: Python Developer's Guide
- API documentation generator: pdoc (for i in *.py; do pdoc --html $i; done), pydoc (for i in *.py; do pydoc -w `echo $i | sed 's/.py//'`; done).
- Static code analysis: pyflakes, pylint (how to use it), pycodestyle, autopep8.
- Code visualizaiton: PyCharm, pyreverse (pyreverse `ls *.py | sed 's/.py//' | tr '\n' ' '`), Python Call Graph, Graphviz it!, webgraphviz, UML tools 2019.
- Testing: unittest, the Python profilers.
- Virtual box: virtualenv (a tool to create isolated Python environments).
- GitHub: Mastering Markdown
- Deployment
  - Python Packages
  - Installing Packages
  - pip freeze, pip install,
  - Packaging Python Projects
  - Python Packaging User Guide
  - An Overview of Packaging for Python
  - Building and Distributing Packages with Setuptools
  - Packaging and distributing projects
  - DLL load failure: CONDA_DLL_SEARCH_MODIFICATION_ENABLE=1 (e.g. NumPy MKL library load failed)
  - PyCharm virtual environment: setting up, venv folder.
  - pip install from local file system folder

Jupyter
- Karlijn Willems. Jupyter Notebook Tutorial.
- A gallery of interesting Jupyter Notebooks.
- Jupyter nbviewer.
SciPy
- scipy-lectures.org: Scipy Lecture Notes.
- SciPy Cookbook.
- docs.scipy.org. NumPy Quickstart Tutorial, NumPy and Scipy Documentation, SciPy Tutorial.
xlwings: Quickstart, video course.
Frequently used libraries:
- argparse: Argparse Tutorial.
- boto3: the AWS SDK for Python developers to use Amazon S3 and EC2.
- config: a hierarchical configuration module
- cx_Oracle: module that enables access to Oracle Database
- datetime: basic date and time types
- functools: for higher-order functions: functions that act on or return other functions.
- howdoi: instant coding answers via the command line.
- json: JSON encoder and decoder
- logging: logging HOWTO, logging cookbook.
- logging.config: logging configuration.
- mysql.connector: MySQL driver
- os: miscellaneous operating system interfaces
- pandas: Python data analysis library, pandas.0.24.1 documentation.
- PythonDoc: API documentation tool, similar to JavaDoc
- requests: an Apache2 licensed HTTP library
- sys: system-specific parameters and functions

Java

Java Mind Map
- A MindMap for Java Developer Interviews
- Java Technology Concept Map
For Java Developers:
- Code visualization: ObjectAid UML Explorer (Youtube tutorial, association-vs-dependency), IBM Rational Software Architect Designer.
- Entity Relationship Diagram: ER Master, ER Diagram Tutorial.
- Java Profiler: JProfiler, YourKit.
- JRebel Resources: Must-Have Cheat Sheets for Java Developers.
- Creating Documentation with javadoc.
- Maven
  - Sonatype. 1) Maven by Example. 2) Maven: The Complete Reference.
  - Balaji Varanasi & Sudha Belida. Introducing Maven. Apress; 1st edition (November 26, 2014). Amazon.
  - Raghuram Bharathan. Apache Maven Cookbook. Packt Publishing (April, 2015).
  - Jason Taylor. Maven Crash Course: Step-by-Step Introduction for Beginners. Last updated 08/2017. Udemy.
  - Maven Central Repository. 1) Repo. 2) Search Engine. 3) Nexus Repository Manager.
  - Apache Maven Project. 1) Maven Documentation. 2) Frequently Asked Technical Questions. 3) Apache Maven Javadoc Plugin. 4) Books and Resources.
  - The Maven 2 POM demystified.
  - Maven Quick Reference Card.
  - Sample pom.xml.
Tutorials & Courses
- TutorialsPoint.com: Eclipse Tutorial.
- GeeksforGeeks: Java Programming Language. (Thread safe Java Singleton design pattern)
- Jenkov.com: Java Date and Time, Java IO (Serializable), Java JDBC, Java JSON, Java Reflection.
- Baeldung: Java, Spring and Web. (A Guide to Java Enums. Attaching Values to Java Enum)
- Oracle. Java Tutorials Learning Paths (for JDK 8).
- Paul Deitel. Java Fundamentals LiveLessons Parts I, II, III, and IV. Prentice Hall (November 17, 2016). informIT.
- Dheeru Mundluru. Java In-Depth: Becoming a Complete Java Engineer. Last updated 10/2018, Udemy.
Desk References
- Cay S. Horstmann: Core Java for the Impatient (Covers Java SE 8). Addison-Wesley Professional; 1 edition (February 12, 2015). Amazon.
- Robert Liguori & Patricia Liguori. Java 8 Pocket Guide: Instant Help for Java Programmers. O'Reilly Median; 1st edition (April 28, 2014).
- Joshua Bloch. Effective Java. Addison-Wesley Professional; 3rd edition (January 6, 2018). Amazon.
- Herbert Schildt. Java: The Complete Reference. McGraw-Hill Education; 10 edition (October 11, 2017). Amazon.
Oracle. 1) Java SE 8 API Specification. 2) Database JDBC API Reference. 3) Java Serialization API.
Apache. 1) Apache Commons Lang 3.9-SNAPSHOT API. 2) Log4j 2 Javadoc API Documentation. 3) Commons Math.

Style Guide: 1) Oracle. 2) Google Java Style Guide. 3) OpenJDK Java Style Guidelines. 4) Java 8 Pocket Guide Naming Conventions. 5) How to Write Doc Comments for the Javadoc Tool.
Angelika Langer. Java Generics FAQs.
Interviews: 150 Java Interview Questions and Answers (ebook), Java Interview Questions, Java Collections API Design FAQ.

Jared P. Lander. R for Everyone: Advanced Analytics and Graphics. Addison-Wesley Professional; 1st edition (December 29, 2013). Amazon.
Jared P. Lander. R Programming LiveLessons. Addison-Wesley Professional, 2013.

Hadley Wickham & Garrett Grolemund. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O'Reilly Media; 1st edition (2017). Amazon.
Winston Chang. Cookbook for R.
Paul Teetor. R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics. O'Reilly Media; 1st edition (March 23, 2011). Amazon.
Winston Chang. R Graphics Cookbook: Practical Recipes for Visualizing Data. O'Reilly Media; 1st edition (January 6, 2013). Amazon.
Hadley Wickham. Advanced R 2ed. Chapman & Hall/CRC; 1st edition (September 27, 2014). Amazon.
Yihui Xie, J. J. Allaire, and Garrett Grolemund. R Markdown: The Definitive Guide. Chapman and Hall/CRC; 1 edition (July 19, 2018). Amazon.
Gang Su: A comprehensive list of handy R packages.
Tidyverse.org. ggplot2 Reference.
RStudio. RStudio Cheat Sheets.
R Language Definition
For R Developers
- Hilary Parker: Writing an R package from scratch, , .
- Fong Chun Chan: Making your first R package
- Hadley Wickham: R Packages
- Make an R Package from Scratch using RStudio.
- Wickham's R style guide
- Miscellaneous: Pass a formula to lm, install packages to a customized directory, install R without admin privileges.

C/C++

Yale N. Patt & Sanjay J. Patel. Introduction to Computing Systems: From Bits and Gates to C and Beyond. McGraw-Hill Education; 2nd edition (2003). Amazon.
Brian W. Kernighan & Dennis M. Ritchie. The C Programming Language. Prentice Hall; 2nd edition (April 1, 1988). Amazon.
Cplusplus.com. C++ Tutorials.
Paul Deitel. C++ Fundamentals I and II LiveLessons (July 2010, Prentice Hall). Safari Books Online.
Stephen Prata. C++ Primer Plus. SAMS; 5th edition (November 23, 2004). Amazon.
Stanley B. Lippman, Josee Lajoie, & Barbara E. Moo. C++ Primer. Addison-Wesley Professional; 5th edition (August 16, 2012). Amazon.
Stephen C. Dewhurst. C++ Common Knowledge. Addison-Wesley Professional (March, 2005). Amazon.
Stanley B. Lippman. Essential C++. Addison-Wesley Professional (November, 1999). Amazon.
Scott Meyers. Effective C++: 55 Specific Ways to Improve Your Programs and Designs. Addison-Wesley Professional; 3rd edition (May 22, 2005). Amazon.
Isocpp.org. C++ FAQ.
Heard at JPMC (2015): C++ Coding Guidelines, C++ Coding Standards.

Shell

Software Carpentry Foundation. Shell Tutorial.
Stanford CS Education Library. Unix Programming Tools.
Bruce Barnett. UNIX SHELL Quote Tutorial.
Cygwin User's Guide.
Mehryar Mohri. [V22.0468-001] Spring 2008 Unix Tools.
Chris Johnson. Pro Bash Programming: Scripting the Linux Shell. Apress; 1st ed. (October 19, 2009). Amazon.
GNU Emacs Manual.

Perl

Greg London. Impatient Perl.
Simon Cozens. Beginning Perl. Perl.org free online Perl books.
James Lee. Beginning Perl. Apress; 3rd edition (April 12, 2010). Amazon.
Gabor Szabo. Beginner Perl Maven. Beginner Perl Maven video course.
Perldoc.perl.org. Manual, Reference, and Modules.

Design Patterns and Software Architecture

Erich Gamma, Richard Helm, Ralph Johnson & John Vlissides. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional (November 10, 1994). Amazon.
TutorialsPoint.com. Design Patterns in Java Tutorial.
Oodesign.com. Design Patterns.
HowToDoInJava: GoF Design Patterns.
BlackWasp: Gang of Four Design Patterns.
Robert C. Martin. Clean Architecture: A Craftsman's Guide to Software Structure and Design. Prentice Hall; 1 edition (September 20, 2017). Amazon.
Robert C. Martin. Clean Code: A Handbook of Agile Software Craftsmanship. Prentice Hall; 1 edition (August 11, 2008). Amazon.
Stanford University. Programming Paradigms (by Jerry Cain, 2008). YouTube.

DevOps

Git Cheat Sheet: Atlassian, GitHub.
John Wiegley: Git from the bottom up.
Jenkins
- Jenkins User Handbook.
- Jenkins User Documentation.
- Jenkins Boot Camp.
- Jenkins 2 Boot Camp.
- Brent Laster. Jenkins 2: Up and Running. O'Reilly Media; 1st edition (May 31, 2018). Amazon.
Russ McKendrick, Pethuru Raj, Jeeva S. Chelladhurai, and Vinod Singh. Docker Bootcamp: The fastest way to learn Docker. Packt Publishing; 1 edition (April 27, 2017). Amazon.
DevOps School.
DevOps Boot Camp.
RebelLabs reports and cheat sheets.
WinDirStat: A disk usage statistics viewer and cleanup tool for Microsoft Windows.

Economics & Economic History

All theory, dear friend, is gray, but the golden tree of life springs ever green. -- Johann Wolfgang von Goethe

EH.net: Measuring Worth.

陕甘宁边区银行纪念馆、《朱理治金融论稿》编纂委员会：《朱理治金融论稿》，北京：中国财政经济出版社，1993。简述
爱德华多·加莱亚诺著，王玖等译，邓兰珍校：《拉丁美洲：被切开的血管》，北京：人民文学出版社，2001。当当网
弗里德里希·李斯特著，陈万煦译，蔡受百注：《政治经济学的国民体系》，商务印书馆汉译世界学术名著丛书（1961年10月）。在线阅读，亚马逊。
Friedrich List. The National System of Political Economy (1841).
张夏准著，严荣译：《富国的伪善》，社会科学文献出版社，2009年1月。当当网
张夏准著，孙建中译：《资本主义的真相——自由市场经济学家的23个秘密》，新华出版社，2011年6月。当当网。
Ha-joon Chang. 23 Things They Don't Tell You About Capitalism. Bloomsbury Press; Reprinted edition (January 17, 2012). Amazon.
Peter E. Kennedy and Jay Prag. Macroeconomic Essentials: Understanding Economics in the News. The MIT Press, 4th edition (August 11, 2017). Amazon.
Peter L. Bernstein. A Primer on Money, Banking, and Gold. Wiley; 1st edition (September 2, 2008). Amazon.

Ib Ravn. Explaining money creation by commercial banks: Five analogies for public education. Real-World Economics Review, Issue No. 71.
张夏准：《反思农业公共政策—历史的经验》，联合国粮农组织，2009。PDF, Word.
Ha-Joon Chang. Rethinking public policy in agriculture: lessons from history, distant and recent. UN FAO, 2009. English original.
威廉·多姆霍夫：《谁统治美国？公司富豪的胜利》，外语教学与研究出版社，2017年。当当网.
William Domhoff. Who Rules America? The Triumph of the Corporate Rich. McGraw-Hill Education; 7 edition (May 17, 2013). Amazon.
赖特·米尔斯：《权力精英》，新华出版社，2017年。当当网
Wright Mills. The Power Elite. Oxford University Press (February 17, 2000). Amazon

Quantitative Finance: General

Alex Kuznetsov. The Complete Guide to Capital Markets for Quantitative Professionals. McGraw-Hill Education (November 22, 2006). Amazon.
Jay Vaananen. Dark Pools and High Frequency Trading for Dummies. For Dummies (February 23, 2015). Amazon.
MIT OpenCourseWare 18.S096: Topics in Mathematics with Applications in Finance, MIT OCW, Fall 2013.
John H. Cochrane. Business 35150: Advanced Investments, University of Chicago Booth School of Business, Winter 2014.

Quantitative Finance: Resources for a Buy Side Fixed Income Quant

Bloomberg Market Concepts. An introduction to the use of the Bloomberg system in swap analysis. Bloomberg Key Functions & Cheat Sheets.
WallStreetPrep. Crash Course in Bonds.
Fabozzi & Mann. Introduction to Fixed Income Analytics, 2nd edition. Amazon.
David Bolder. Fixed-Income Portfolio Analytics. Amazon.
Robert S. Kricheff. A Pragmatist's Guide to Leveraged Finance: Credit Analysis for Bonds and Bank Debt. FT Press (March 2012). Amazon.
Arik Ben Dor, Leve Dynkin, Jay Hyman, and Bruce D. Phelps. Quantitative Credit Portfolio Management. Wiley 2011. Amazon.
Portfolio Visualizer.

Quantitative Finance: Resources for a Fixed Income Pricing Quant

Static Data
- Holiday Data: Copp Clark.
- Day count conventions: wikipedia, treasures.org, NASDAQ, OpenGamma Strata.
- Instrument conventions: OpenGamma Interrest Rate Instrument and Market Conventions Guide.
- Reference Data: FINRA Bonds.
- Paul Miron and Philip Swannell. Pricing and Hedging Swaps. Euromoney Books (1991). Amazon.

Market Data
- USD: Federal Reserve H.15 Selected Interest Rates.

Marc Henrard. Interest Rate Modelling in the Multi-Curve Framework: Foundations, Evolution and Implementation. Palgrave Macmillan (2014). Amazon.

OpenGamma Quantitative Research
Bloomberg
- Bloomberg Market Concepts.
- Bloomberg Open API Library Support, BLPAPI Documentation.
- Curves
  - The New Swap Math.
  - OIS Discounting and Dual-Curve Stripping Methodology at Bloomberg.
  - Extending USD OIS Curves Using Fed Funds Basis Swap Quotes.
  - Building the Bloomberg Interest Rate Curve -- Definitions and Methodology.
  - Default-Adjusted Par Curves.
  - OIS Framework through BVAL Derivatives.
  - Overview of Bloomberg Models for Interest Rate Derivatives in DLIB.
Numerix
- Curves
  - A Note on Constructing Treasury Yield Curves.
  - USD Multi-Curve Construction: Bootstrapping vs. Global Solving.
  - Expanded View: Interpolation Methods in CorssAsset.
Kalotay: BondOAS Library Overview, BondOAS Library API Documentation.
FinPricing: Knowledge is Power

Pursuing a PhD?

Robert Peters: Getting What You Came For: The Smart Student's Guide to Earning an M.A. or a Ph.D. (April 11, 1997). Amazon, Summary.
Andrej Karpathy: A survival guide to a PhD
Philip Guo: A Five-Minute Guide to Ph.D. Program Applications, The Ph.D. Grind.

Last updated: 2020-08-04

Summaries for Quantitative Finance

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