Quantitative Finance Resources

Datasets

  1. Quandl: page (stocks guide 1, stocks guide 2)
    1. Python api
    2. Browse databases
    3. Premium content
  2. Google Finance (page)
  3. Yahoo Finance (page)
  4. Kaggle
    1. Winton Stock Market Challenge (page, data)

Software/Frameworks

  1. Quantopian (main, github)
  2. Python with Finance
    1. Dx Analytics (main, github)
    2. Python for Finance (page)
    3. Derivative Analytics with Python (page)
    4. Quant Platform (page)
    5. Python Quants (page)
  3. QSTK (page, github)
  4. Quantlib (page, github)
  5. Investopedia (page, simulator)

Videos/Courses

  1. Computational Investing Part 1 – GT – Coursera Page
  2. Machine Learning for Trading – GT – Udacity Page
    1. Intro material (youtube playlist)
    2. Machine learning (youtube playlist)
  3. UW – Intro to Computational Finance (Cousera)
  4. Quantopian (Getting Started)
  5. Sentdex
    1. Python for Finance with Zipline and Quantopian (youtube playlist)
    2. Scikit-learn ML with Python (youtube playlist)
    3. Programming to aid Fundamental Investing (youtube playlist)
    4. ML for Forex, Stock Analysis, Algo Trading (youtube playlist)
    5. Big Data with Stock Trading (youtube playlist)
    6. Monte Carlo Python (youtube playlist)
    7. Matplotlib (youtube playlist)
  6. Python Quants (page)
    1. 2014 For Python Quants (playlist)
  7. Cousera – Michigan
    1. Principles of Valuation: Time Value of Money (page)
    2. Risk and Return (page)
    3. Alternative Methods (page)
    4. Projects and Companies (page)
    5. Capstone (page)
  8. Cousera – Chicago – Asset Pricing
    1. Part 1
    2. Part 2
  9. Quantlib
    1. vimeo page, youtube playlist
    2. ebook
    3. twitter
    4. Implementing Quantlib (blog)
    5. Examples in python, blog
  10. Coursera – Wharton
    1. Quant Modeling (page)
    2. Spreadsheets & Models (page)
    3. Risk Models (page)
    4. Decision Making and Scenarios (page)
    5. Capstone (page)
  11. Cousera – Columbia
    1. Financial Engineering and Risk Management I (page)
    2. Financial Engineering and Risk Management II (page)
  12. Khan Aademy
    1. Valuation and Investing (youtube playlist)

Methods

  1. Sentiment Analysis
  2. Machine Learning
  3. Deep Learning
  4. MDPs, RL, and QL

Books

  1. Hull (Options, Futures, and Other Derivatives (10th Edition) on Amazon)
  2. R Cookbook (Amazon)

Papers

  1. ArXiv – Q-fin, Qfin recent, twitter
    1. q-fin.CP – Computational Finance (new, recent, current month)
      Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
    2. q-fin.EC – Economics (new, recent, current month)
      Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside of finance
    3. q-fin.GN – General Finance (new, recent, current month)
      Development of general quantitative methodologies with applications in finance
    4. q-fin.MF – Mathematical Finance (new, recent, current month)
      Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
    5. q-fin.PM – Portfolio Management (new, recent, current month)
      Security selection and optimization, capital allocation, investment strategies and performance measurement
    6. q-fin.PR – Pricing of Securities (new, recent, current month)
      Valuation and hedging of financial securities, their derivatives, and structured products
    7. q-fin.RM – Risk Management (new, recent, current month)
      Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
    8. q-fin.ST – Statistical Finance (new, recent, current month)
      Statistical, econometric and econophysics analyses with applications to financial markets and economic data
    9. q-fin.TR – Trading and Market Microstructure (new, recent, current month)
      Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making

People

  1. Ipython Quant blog

Groups

  1. Reddit
    1. Algotrading Reddit
    2. Investing Reddit
    3. Stock Market Reddit
    4. Stocks Reddit
    5. Forex Reddit
    6. Finance Reddit
    7. Bitcoin Reddit
    8. Bitcoin Markets Reddit

Docker/AWS

  1. Quantlib (docker images)
  2. QSTK
    1. ipython docker image
    2. ontouchstart docker image
    3. Twisted logic docker image
  3. BitQuant docker image

Terms

  1. Mathematical Finance (Wikipedia pageWikipedia subject)
  2. Alpha
  3. Beta
  4. Sharpe Ratio
  5. Bollinger Bands
  6. Drawdown
  7. SMA (crossover)
  8. CAPM
  9. Options
  10. Futures
  11. Forex

 

 

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