Benford Lesson #2
At first I only used the #1 because it was the most prevalent and moved around the most. I began by seeing what would happen if the #1 got really far away from its ideal level of 31.8% but it was not clear enough to trade from. Oftentimes when it did reach and stay close to its 'ideal level' of 31.8%, the market would just stop moving.
But this told me something as well. It told me that without "big money" and highly dominant players overtaking the the "natural order," markets will not move much. We need these folks. Problem is, they expertly mask their operations. You will NEVER see their actions in the volume or in anything else. That's how good they are. Make no mistake. They are the BEST at what they do. They spend millions of dollars on salaries, the most powerful computers and the brightest and best minds in order to maintain an edge. Whatever you think you see of them is because they want you to see it.
God bless em!
I don't know who these heavy hitters are. It could be various banks, large hedge funds or whatever. The "who" isn't important. What is important is that these folks invest enough capital to obliterate the "natural order" of the markets. The capital outlay must be considerable indeed! It would have to be in the billions.
We want to trade on the same side they do. Their capital outlay is considerable; therefore, their reasons for putting on positions where they do are considerable as well. Let them do some of our work for us. Let's use their research and opinions.
Finding the Ideal Extremes
Since the distribution of numbers are seldom at their ideal levels, another means of finding "unlikely events" had to be found. There had to be a reliable, yet frequent enough of an event to be of use.
This is why I finally landed on the intersection of #1 and #4. Recall earlier (and in the chart in the previous post), that the #4 should occur around 9% of the time. To have #1 and #4 intersect is a very unlikely event. Either #4 has to increase by 22%, or over 200% its normal distribution, or #1 has to decrease its normal distribution by roughly 72%.
At first I only used the #1 because it was the most prevalent and moved around the most. I began by seeing what would happen if the #1 got really far away from its ideal level of 31.8% but it was not clear enough to trade from. Oftentimes when it did reach and stay close to its 'ideal level' of 31.8%, the market would just stop moving.
But this told me something as well. It told me that without "big money" and highly dominant players overtaking the the "natural order," markets will not move much. We need these folks. Problem is, they expertly mask their operations. You will NEVER see their actions in the volume or in anything else. That's how good they are. Make no mistake. They are the BEST at what they do. They spend millions of dollars on salaries, the most powerful computers and the brightest and best minds in order to maintain an edge. Whatever you think you see of them is because they want you to see it.
God bless em!
I don't know who these heavy hitters are. It could be various banks, large hedge funds or whatever. The "who" isn't important. What is important is that these folks invest enough capital to obliterate the "natural order" of the markets. The capital outlay must be considerable indeed! It would have to be in the billions.
We want to trade on the same side they do. Their capital outlay is considerable; therefore, their reasons for putting on positions where they do are considerable as well. Let them do some of our work for us. Let's use their research and opinions.
Finding the Ideal Extremes
Since the distribution of numbers are seldom at their ideal levels, another means of finding "unlikely events" had to be found. There had to be a reliable, yet frequent enough of an event to be of use.
This is why I finally landed on the intersection of #1 and #4. Recall earlier (and in the chart in the previous post), that the #4 should occur around 9% of the time. To have #1 and #4 intersect is a very unlikely event. Either #4 has to increase by 22%, or over 200% its normal distribution, or #1 has to decrease its normal distribution by roughly 72%.