Larry Connors’ Daily Battle Plan: Getting into ETF Trades 101
A market that has been rallying for day after day after day suddenly stops, reverses and begins to pull back. If you are a high probability trader, then you know that this is the kind of market environment you have been waiting for. Moreover, you’ve subscribed to Larry Connors’ Daily Battle Plan and have read a Market Intel report that points to a pair of ETFs that have become exceptionally oversold.
Maybe the ETFs have fallen for two days in a row and are looking likely to close down for a third. Maybe the ETFs have developed 2-period RSIs of less than 15 – or even less than 5. Maybe the ETFs have earned ETF PowerRatings upgrades to 9. Or even 10. Whatever the reason, you arrive at the Battle Plan home page and after perusing the market analysis, you read this line:
“Buy the first of potentially up to three units in … if the ETF closes lower today.”
That line is the “gentlemen start your engines” of high probability ETF trading in Larry Connors’ Daily Battle Plan. And as of October 2009, those engines are roaring. Since adding ETF trading to the Daily Battle Plan a year ago, the service has gone 42-8. Our most recent trade, a play on the ^FXI^ in early October, gained nearly 5% in a matter of days.
Let’s take a look at the three main components of high probability ETF trading in Larry Connors’ Daily Battle Plan. Understanding how these components work is critical to making the most out of the service and to keeping the edges on your side as a high probability trader..
“Buy the first …”
High probability ETF trading in Larry Connors’ Daily Battle Plan is about buying pullbacks in trends. Our quantified approach to trading tells us that we should look to buy our first piece of a high probability ETF position AFTER the ETF has become oversold above the 200-day moving average. Conversely, if you are looking to sell short, then your strategy is to sell short the first piece of a high probability ETF position AFTER the ETF has become overbought below the 200-day moving average.
Above, a Battle Plan long trade from early September in the ^EWH^. A gain of nearly 5% in three days.
” … of potentially up to three units …”
One of the more impressive discoveries of our high probability approach to short term trading of ETFs is the fact that by scaling-in to positions, buying more shares as the ETF trades lower, traders can dramatically boost returns.
Because ETFs – especially country and equity index ETFs – have a pronounced tendency to revert to their mean, high probability traders can get an edge when buying additional shares as the ETF becomes more oversold, straying farther and farther from their mean or average price. This tendency can be so strong that in some instances a trader will see larger gains from the final piece of an ETF position than they might from all the other, earlier scale-ins combined.
Up more than 5% in less than 5 days, this short trade was one of the bigger winners in the Larry Connors’ Daily Battle Plan this spring.
“… if the ETF closes lower today.”
Our strategy when buying ETFs for high probability trades is to take positions on the close. In the same way that we look for intraday weakness to take positions when buying stocks on pullback, we want to see ETFs that we are interested in buying close at their oversold extremes. This is a way of assuring – as much as possible – that we are truly “buying the selling” and taking as much advantage as possible of the historical edges that support buying oversold markets and selling overbought ones.
Isn’t it time you gave the high probability ETF trading strategies of Larry Connors’ Daily Battle Plan a try? Click here to launch your free, 7-day trial today. After 50 high probability ETF trades with 42 profitable exits over the last year, this is the kind of trading edge that more short term traders need to know.
80% winning trades! Find the best ETF setups with Larry Connors’ Daily Battle Plan, a highly accurate trading service with daily entry and exit signals for ETFs. Get your free 7 day trial now – Click Here.
Originally published Oct 13, 2009