Topics in Quantitative Finance

This web page links to various sub-pages that discuss topics in quantitative finance.

Most people have not heard of quantitative finance or, if they have, they seem to recall that it was bad models that helped to crash the financial system in 2008. Few people who are not finance professionals or those who study finance at a University realize how large the field is.

The size and complexity of quantitative finance makes writing tutorial material difficult in anything less than book length. These web pages assume familiarity with graduate level quantitative finance. Someday perhaps I will be able to write a book which does a better job of explaining some of this material, but these web pages are, at most, a seed for this larger project.

Investment Portfolio Construction

• Value Factors Do Not Forecast Returns for S&P 500 Stocks

  Value Factors Do Not Forecast Returns was my degree project for my University of Washington Computational Finance and Risk Management degree.

• The global minimum variance and tangency portfolio equations

• Long/Short CVaR Portfolio Optimization

• ETF Portfolios

  • A Portfolio of Exchange Traded Funds (2012)

  • Building an Exchange Traded Fund Portfolio (2014)

  • All Weather Investment Portfolio

  • A Dividend Investment Portfolio

  • The Twelve Percent Portfolio

• Using Options Implied Volatility to Predict Returns

• Factor Models

Data

Data is the life blood of finance. Even in the case of options pricing, which is the most theoretical and model based area of finace, options market data provides the implied volatility for an option. In most other areas of finance nothing can be accomplished without data.

Perhaps because data is so critical to the ability to make money, especially in quantitative finance, data costs money. For those in the academic community, financial data can be obtained from the Wharton Research Data Serivce (WRDS).

• Building the S&P 500 Index Constituents

• The Wharton Research Data Service (WRDS) data set and Factor Model Factors

Miscellaneous

• Smoothing a Time Series with a Kalman Filter in R

• Random R Hacks

Java Code

• Lattice Pricing in Java Lattice pricing of stock options, written in Java. This includes a hack for pricing a "chooser options" (also know as an "as-you-like-it" option).

• A Java intra-day trading system, quantitative finance, technical analysis and other topics.

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