quant trading strategies - How are cryptography and speech recognition technology applied to forecasting financial markets?

One of the answers to my previous question regarding the strategy of Renaissance Technologies, there was a reference to The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It.

After doing some browsing in the book I found that it states that Renaissance Technologies obviously very successfully employs cryptography and speech recognition technology for forecasting financial time series.

Do you know of any good papers (or other references) where the use of either of these technologies in connection with finance is shown?

Answer

By "cryptography" you mean information theory. Information theory is useful for portfolio optimization and for optimally allocating capital between trading strategies (a problem which is not well addressed by other theoretical frameworks.)

See:

--- J. L. Kelly, Jr., "A New Interpretation of Information Rate," Bell System Technical Journal, Vol. 35, July 1956, pp. 917-26

--- E. T. Jaynes, Probability Theory: The Logic of Science http://amzn.to/dtcySD

--- http://en.wikipedia.org/wiki/Gambling_and_information_theory

In the simple case, you would use "The Kelly Rule". More complicated information theory based strategies for allocating capital between trading strategies take into account correlations between the performance of trading strategies and the relationship between market conditions and strategy performance.

As for Natural Language Processing and speech recognition; when you examine the founders of Renaissance Technology, you will notice that many of the early employees had backgrounds in natural language processing. Naively, you might assume that RT is using NLP based strategies.

However, you will find that all of RT's NLP related hires have backgrounds (published research, Phd thesis's) in speech recognition and specifically in Hidden Markov Models and Kalman filters. The academic background and published research of RT employees gives you a good idea of the algorithms they are using.

The information that has leaked out of RT suggests that RT heavily uses "hierarchical hidden markov models" for latent variable extraction from market time series. It is also believed that RT has developed a proprietary algorithm for "layering" multiple trading strategies for trade signal generation.

RT does not have a single secret trading strategy that magically generates billions of dollars a year. Renaissance Technology's trading strategies are based upon the integration of information from multiple mathematical models.