I’ve spent the past three weeks developing my first trading system: a value-influenced mean reversion strategy that includes causal variables for hedge fund activism and political risk. Here are 10 books I used as part of the development process for my first trading system:
1. Jeff Madrick’s Age of Greed: The Triumph of Finance and the Decline of America, 1970 to the Present (Alfred A. Knopf, 2011). Madrick’s overarching history of Wall Street provides detail on central bank, monetary policy, political administration, industry sector, and deal flow variables. It’s also great investigative journalism that gives a deep historical background to what capital and financial markets are really like.
2. John Heins & Whitney Tilson’s The Art of Value Investing: How the World’s Best Investors Beat the Market (Hoboken, NJ: John Wiley & Sons, 2013). I started with value investor wisdom for the initial idea development and possible decision rules. Heins & Whitney’s investment newsletter interviews gave me plenty of examples for inductive data coding.
3. Anti Ilmanen’s Expected Returns: An Investor’s Guide to Harvesting Market Rewards (Hoboken, NJ: John Wiley & Sons, 2011). Ilmanen was one of the first sources I consulted to understand the historical return drivers of equities as an asset class, and its inter-market relationship with other common asset classes.
4. Andrew W. Lo’s Hedge Funds: An Analytic Perspective (rev. ed.) (Princeton, NJ: Princeton University Press, 2011). Hedge fund activism that shapes equities asset prices is a key causal variable for the mean reversion strategy. Lo’s research highlights some hedge fund trading patterns and shows how to draw inferences from databases and market data.
5. Keith Fitschen’s Building Reliable Trading Systems: Tradable Strategies That Perform as They Backtest and Meet Your Risk-Reward Goals (Hoboken, NJ: John Wiley & Sons, 2013). I’ve read several books that go back a decade on mechanical, automated and algorithmic trading systems. Fitschen highlights mean reversion and momentum strategies, and the importance of robust backtesting with both in-sample and out-of-sample market data.
6. Richard Tortoriello’s Quantitative Strategies for Achieving Alpha (New York: McGraw-Hill, 2009). Tortoriello’s book is essentially a collection of factor models and quantitative screens that uses a Standard & Poor’s rating methodology. Factor models help to isolate the potential alpha of return drivers from the market beta.
7. Barry Johnson’s Algorithmic Trading & DMA: An Introduction to Direct Access Trading Strategies (London: 4Myleoma Press, 2010). Johnson covers the importance of market microstructure, early developments in algorithmic and high-frequency trading, and the importance of transaction and execution costs. Several publishers are releasing new books about these topics in the second half of 2013.
8. Aaron C. Brown’s Red-Blooded Risk: The Secret History of Wall Street (Hoboken, NJ: John Wiley & Sons, 2012). Brown is a risk manager with AQR Capital Management. One of the many insights I took from this book was the importance of risk ignition in ‘live’ testing of a trading system, and in considering exit signals.
9. Ari Kiev’s The Mental Strategies of Top Traders: The Psychological Determinants of Trading Success (Hoboken, NJ: John Wiley & Sons, 2010). The late Ari Kiev was an influential sports performance and trading psychologist who consulted with Steve Cohen’s SAC hedge fund. He has written several best-selling books on trading psychology. This book deals with expectational analysis and variant perception (Michael Steinhardt) which frames the entry signals and filters that a trading system must have.
10. John Coates’ The Hour Between Dog And Wolf: Risk-Taking, Gut Feelings, and the Biology of Boom and Bust (London: Fourth Estate, 2012). Coates’ personal research program combines ‘live’ trading experience and neurophysiological studies. Extremely useful information on the human stress response, mental toughness, and risk stressors that can shape ‘live’ trading or the ‘live’ discretionary over-ride of algorithmic trading systems.
Hedge fund and trading system architecture is expensive, and beyond the reach of the retail investor. However, investment in the above books (US$345.32 from Amazon.com at the time of original publication) may give a glimpse of what is possible, from initial idea development (value-based mean reversion) to backtesting, ‘live’ trading, and possible algorithm coding. It’s the information you select; the processes you use; and how your alpha return drivers support the trading system that results from research development, backtesting, and ‘live’ trading.