Dark Pools (Book Review)

Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market by Scott Patterson has been one of the most interesting books I've read this year on the subject of high frequency trading. It explains the history of US exchanges going from floor to electronic, and some of the key (and awesome) people who helped shape the trading environment today.
  





Some key players

Haim Bodek: A star developer/trader at Hull/Goldman, who specialized in options market making. The book explains his experience at Trading Machines being picked off by competing algorithms due to microstructure disadvantages.

Joshua Levine: Mentioned in "Top 10 Financial Technology Innvators of the Decade", this is a t-shirt and jeans computer science genius who created Island ECN, which effectively changed the way NASDAQ stocks were traded, and broke up the floor market makers' control over order flow of the old days. He still updates his blog at wp.josh.com.

GETCO: Now part of KCG Holdings, GETCO was founded by a couple of ex-floor traders Stephen Schuler, Daniel Tierney who understood the potential of electronic trading, and has been one of the most successful firms who specialize in Automated Market Making (AMM). It was estimated in 2007 that their average daily net profit had averaged about $7M USD.

Key money making strategies mentioned

Market Making & high speed arbitrage off exchange microstructure inefficiencies. The book explores tenets around these core principles, and examples of those who had successfully implemented them.

The Speed Traders (Book Review)

I went through The Speed Traders: An Insider's Look at the new High-Frequency Trading Phenomenon That is Transforming the Investing World by Edgar Perez at the AUT Library earlier in the week. The book felt somewhat entertaining, not-so-informative for anyone with industry experience, and there was excessive moot around ethical opinions.

History of HFT

So it all started out with firms or departments who specialized in arbitrage, without any particular theoretical edge, needing speed. As competition grew, everyone relocated closer to the exchanges and the rest is history.

Trading Strategies

There are only 3 main categories of strategies involved.

1. Pure Classical Arbitrage
2. Buy-side / Sell-side Execution Algorithms (e.g. buy side at Knight Capital)
3. High Frequency Statistical Arbitrage /  Automated Market Making

There is a ton of individual strategies/opportunities within each category. The "simplest" category is of course pure arbitrage, and the most complex being Statistical Arbitrage where a robust, theoretical edge must be established.

Is speed alone enough?

No. Competition in this industry is extremely fierce. With big players like Getco spending $2M~/month on IT infrastructure, it isn't feasible to expect any significant edge in strategies heavily dependent on speed.

Market Microstructure Theory by Maureen O'Hara (Book Review)

Market Microstructure Theory preview




Efficient Market Hypothesis is obsolete, Market Microstructure Theory is what's relevant for today's high tech Wall St. scene. Despite the age of this book (1995), the author provides some solid theory and analytical models for the serious market participant. 

Interesting points from the book

Coming from an academic, O'Hara displays a very deep understanding of financial trading along with the nature of price evolutions and "The Nature of Markets". She explores behavior models of market makers, informed, and uninformed traders with respect to auction types utilized.

Inventory Management is a big issue for market makers, or really anyone who applies strategies involving position accumulations.

Game Theory is touched upon, as expected in today's algorithmic trading scene, as big players attempt to outwit each other.

Prerequisites to understanding the models

The models do get relatively technical. This book requires an intermediate understanding in microeconomics, deep understanding in statistics, and some matrix calculus.


Overall conclusion


Though I don't believe the models themselves provide money making solutions directly. Understanding how they work, and figuring out ways to remedy their shortcomings could lead to some brilliant thoughts around trading today's tough markets. Nevertheless, it's an interesting read if anything.