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By using the fractal relationships of the 10, 30, 90, and 270-period linear regression lines we get a view of how market participants on different timeframes with very different agendas are interpreting price action. We also can start to get a feel of the breath of the market’s cycles of expansion and contractions and how the extreme conditions of large stretches and tight pinches of the regression lines can alert us to the potential of some fantastic opportunities.
The next indicator we can add to our toolkit is the 30-Period Linear Regression Line, aka the “RL30”. As would be expected, the RL30 is similar to the RL10 but is based on 30 periods of price data. This makes it three times slower than our RL10 indicator. A simple difference, but the implications and uses of this simple change shouldn’t be underestimated.
This is precisely what we do in the Owl Group following Dr. Ken Long’s style of trading when we use the 10-Period Linear Regression Line (dubbed the “RL10” for brevity’s sake). We know we’re going to be susceptible to all sorts of heuristics and biases in analyzing price information, so why not have a highly effective and efficient and robust single indicator we can apply to any timeframe and financial instrument.
In the art of trading, self-discipline is the key to success. Drawing inspiration from the Monkey King and Guanyin, we can learn to emphasize the importance of a concise trading plan, trading in sample sets, and maintaining a meticulous trade journal. Like mastering any craft, trading requires continuous improvement and a commitment to self-discipline. By measuring progress against personal goals and staying true to a well-defined plan, traders can navigate the market with the skill and finesse of the Monkey King himself.
Knowing we were in a downward-trending market gave us an additional edge and a higher probability of the trade working in our favor. The main takeaway from appreciating the value of variation in market data is to be aware of the fluctuations in the overall market, have a reliable method to gauge and measure these variations, and develop a systematic approach to exploit them. By incorporating these principles into their trading strategies, traders can position themselves to capitalize on the dynamic nature of the market and potentially achieve more favorable trading outcomes.
In this article I would like to share our student’s trade results from our Applied Systems Development course trading assignments. We provide instruction during our classes and encourage students to independently apply the taught rules and principles on their own trading platforms throughout the week.
Today I’d like to go through an example of how we can use our logic chain concept to do a top-down analysis of the market to find symbols in a critical state that we can be ready to trade the next day. In the Owl Group we use a “plan, prepare, execute, assess” process for trading in a systematic and professional way. A large part of the ‘prepare’ phase consists of having reliable ways to find targets.
One of the best uses of the laconic management technique I have used in my own trading is simplifying my ruleset. I have often had a struggle of values with trading rulesets where one part of me wants to have complex rules with a contingency for every plan. And the other part wants to have simplified rules that might not have every scenario mapped out, but because of the simplicity of them my effectiveness in execution can be almost flawless. The psychological benefit of being able to execute a ruleset perfectly really can’t be overstated. And this has allowed me increase span of control very easily when I take the approach of an ‘easy peasy’ rule set.
Using data in trading is a fascinating experience for me. Like many things in life, I believe it’s the art of striking a balance. I need data in order to trade and in order to analyze my trading results. You could say the whole process of trading and financial instruments can be reduced to data points. It is just price, after all. But what’s so interesting to me is that I know from experience it’s not always about more data.
I have found the diligent use of finding estimated reward targets to be one of the most overlooked aspects of trading. Most traders will know when they plan to enter. And most will know when they want to get out with an initial stop point if the trade doesn’t work. But finding the estimate target area is just as important because that is what creates the low-risk idea, the possibility of the asymmetrical return.
The Kata Challenge System is a trading system developed by Dr. Ken Long with traders at Ablewaytech.com that helps traders become more successful. The system is based on the concept of "katas," which are pre-defined trading patterns that capture all the major price moves in the market. The system uses a combination of technical analysis and risk management to identify profitable trades and minimize losses. It emphasizes the principles of commitment, discipline, study and simplicity to teach how to trade professionally.
In this article I’d like to talk about the process of finding symbols to trade each day. This can be applied to any timeframe really, because whether I’m conscious of it or not I have some reason for selecting a symbol to trade. Whether I plan to hold it for ten years or ten minutes, there was some thought process I went through to decide on that symbol.
