There is a brand new format in the Extended Learning Track-Momentum Intraday Trading course. This new format allows us to work together with our students to identify and capture high probability trading opportunities in equities.
Having the opportunity to provide leadership and direction for the XLT program going forward, I would like to share how we have modified the XLT-Momentum Intraday Trading course in order to better prepare our XLT students for each trading day before the market opens.
New Session Times
Previously, XLT-Momentum Intraday Trading sessions started after the stock market opened, which was fine and safe for new traders. With our new format, trading and analysis sessions start thirty minutes before the stock market opens and here is why. It is VERY important that our student-traders set up as many of their day trades in advance as they can. The process that leads to low risk and high probability trading is to first identify support (demand), resistance (supply), and the trend in the S&P and the NASDAQ. Once we know where these high probability turning points are in the governing markets (S&P and NASDAQ), we then scan for stocks with demand and supply levels that line up with the S&P and NASDAQ to help stack the odds in our favor.
Finding Market Turning Points
Step one is to identify high probability demand and supply levels in the governing markets. Let’s take a look at a day last week in the XLT-Momentum Intraday Trading. During a recent session on January 21st, we identified that the S&P was going to open just below a supply level. We marked the level with two lines to create a “supply zone”. Given that we now knew where the high probability turning point was in the S&P, our next task was to look for stocks with supply levels that also lined up with the S&P supply level.
Finding the High Odds Candidates
Below is a chart of Google. After identifying the S&P supply level, we found that Google had a supply level that lined up with the S&P area. Google was opening well below its supply level but that’s okay. The Google supply level was very ideal. Notice how price initially collapsed from the level. This rapid decline suggests a major supply and demand imbalance at that level meaning many more willing sellers than buyers. In the XLT, we pay close attention to the demand and supply levels that have a rapid move away from them as that means very high probability.
When the S&P rallied up to its supply level, so did Google and in strong fashion. This created a very high probability shorting opportunity which worked out very well and very quickly. Again, timing your equity trades with the S&P or NASDAQ supply and demand is the key to high odds trading.
RIMM was another shorting opportunity that lined up with our S&P supply. For those who wanted the same opportunity as Google but in a much cheaper stock, RIMM was a perfect choice. RIMM also had a nice profit margin as demand was around $1.50 below our entry point to sell short. Risking $0.50 to make at least $1.50 to our first target gave us an ideal reward to risk of 3:1. The probability of this trade working out was huge because this supply level lined up with S&P supply.
Learn, Trade, Learn, Trade…
Another change to the XLT-Momentum Intraday Trading course structure has been to alternate between lesson-based sessions and trading-based sessions. We learn, then we trade, then we learn, then we trade, and so on. The lessons are a series of building blocks that first teach our XLT students how to quantify demand (support) and supply (resistance) and then move into rule-based strategy lessons. XLT-Momentum Intraday Trading, and all of our XLT courses for that matter, are not about extra effort and learning tons of information. It’s about putting all the information students learn in the physical classroom at their local center and applying those concepts and tools in such a way that will result in becoming a consistently profitable trader.
If you have any questions about this new and exciting program, email me or your Education Counselor. Have a great day.
– Sam Seiden (firstname.lastname@example.org)