Statistical Arbitrage Based on No-Arbitrage Dynamic Term Structure Models
Author: Liuren Wu, Zicklin School of Business, Baruch College
Date: Fall 2007
This 67 slide presentation introduces statistical arbitrage from a fixed income perspective. In addition, the concept of risk neutrality is derived and explored in a useful way.
Testing Market Efficiency Using Statistical Arbitrage with Applications to Momentum and Value Strategies
Authors: Steve Hogan, Robert Jarrow, Melvyn Teo, Mitch Warachka
Date: June 8, 2004
Publisher: Journal of Financial Economics 73 (2004) 525-565
This academic paper focuses more on whether the existence of statistical arbitrage is incompatible with market efficiency and less no actually identifying and exploiting statistical arbitrage opportunities. Nonetheless, it is an important article in that it lays the mathematical ground work for statistical arbitrage and in includes an extensive list of references.
The Statistics of Statistical Arbitrage
Authors: Robert Fernholz and Carie Maguire Jr.
Date: September/October 2007
Publisher: Financial Analysts Journal, CFA, Volume 63 , Number 5
This brief paper argues that a specific flavor of statistical arbitrage can achieve high information ratios even when using relatively naïve techniques. In the appendix, the authors develop a model for a stock price process with trading noise.
Understanding the Profit and Loss Distribution of Trading Algorithms
Authors: Robert Kissell and Roberto Malamut
Date: February 2005
Publisher: Institutional Investor: Guide to Algorithmic Trading
The authors, both of whom work at JP Morgan, are well regarded in the field. Kissell is also the co-author of Optimal Trading Strategies. Written for an institutional investor audience, this brief paper describes an analytical process to assess the impact parameter choices have on the profit and loss distribution of an algorithm.