Short Term Trading Strategies That Work PDF
“Short Term Trading Strategies That Work: A Quantified Guide to Trading Stocks and ETFs” by Larry Connors and Cesar Alvarez, published in 2009, offers a data-driven approach to mastering short-term trading. Drawing from Connors’ experience as a professional trader since 1994, this book presents 16 backtested strategies (1995-2007) for stocks and ETFs, emphasizing mean reversion and momentum. Key tactics include buying pullbacks instead of breakouts, trading above the 200-day moving average, leveraging the VIX for fear and greed signals, and using the 2-period RSI as a near ‘holy grail’ indicator. With rules like the Double 7’s and end-of-month strategies, it challenges conventional wisdom, advocating wider stops and overnight holds for better returns. Supported by statistical evidence, this guide equips traders with practical, proven methods to navigate the market’s complexities profitably.
Excerpts
“The one thing [professional traders] have in common is that they know what it’s like to trade
from a position of strength. Each has the institutional and floor experience to fully understand that in order to consistently make money from the market, they want to buy into the selling and sell into
the buying.”
“They followed their dream and have become successful because of their brains and most importantly their tenacity.”
“…the never ending challenge of figuring out a game that may be the most complex and fascinating game in the world. It’s a game with a fixed set of rules, but with the pieces always moving.”
“Philosophically, I live in a world of reversion to the mean when it comes to trading. What that simply means is that something stretched too far will snap back.”
“First we’ll look at certain behavior which is inherent in the marketplace. …You will learn that what seems to be logical and obvious is often wrong when it comes to trading.
“It’s one thing for someone to give you a handful of rules and say “trust me, this works.”” It’s another thing to have it backed up by statistical evidence.