December 2009
Intermediate to advanced
352 pages
8h 47m
English
book
High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
by Irene Aldridge
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Chapter 13. Statistical Arbitrage in High-Frequency Settings
Statistical arbitrage (stat-arb) exploded on the trading scene in the late 1990s, with PhDs in physics and other "hard" sciences reaping double-digit returns using simple statistical phenomena. Since then, statistical arbitrage has been both hailed and derided. The advanced returns generated before 2007 by many stat-arb shops popularized the technique. Yet some blame stat-arb traders for destabilizing the markets in the 2007 and 2008 crises. Stat-arb can lead to a boon in competent hands and a bust in semi-proficient applications.
The technique is a modern cousin of a technical analysis strategy utilizing "Bollinger Bands" that was used to indicate maximum highs and lows at any given point in time by plotting a two-standard deviation envelope around the simple moving average of the price. Despite the recent explosive popularity of stat-arb strategies, many misconceptions about the technique are prevalent. This chapter examines the stat-arb technique in detail.
At its core, stat-arb rests squarely on data mining. To begin with, stat-arb analysts sift through volumes of historical data with the objective of identifying a pervasive statistical relationship. Such a relationship may be between the current price level of the security and the price level of the same security in the recent past. The relationship may also be between price levels of two different securities, or the price level of one security and the volatility of ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.