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MENTORING - Market Profile - Introduction - Coggle Diagram
MENTORING - Market Profile - Introduction
A market generates a price at every tick. That means it generates a huge amount of data.
A market price is a constant on a historical basis, but is a function of various prices on a future basis (not futures contracts).
Instead of looking at the market as one price, we should start looking at the market as a set of prices. or a range of prices.
If we observe market data as a set of data, we have some good tools that can give some meaningful information.
This way of looking at the market is far better than looking at it as one price.
If we look at as a set of data, it is meaningless if we have to analyse all the data points. So we will take help form statistics to narrow down our problem.
In statistics, large swathes of data are analysed in a methodical manner by understanding/fitting them into some kind of distributions.
What we mean by a distribution is to understand the nature of the data and its behavioural properties.
Unless you understand the distribution properties of a data set, you cannot solve the problems.
Statisticians have long worked on all kinds of data and segregated them to the distributions appropriate for them.
Statisticians have found that financial asset prices, especially stocks, and their returns are always following a Normal Distribution.
In a Normal Distribution, most of the data points are clinging around a particular centre. This is called the property of centrality.
In a Normal Distribution, the data points are spread over a particular distance from that centre. This is called the property of dispersion.
Peter Steidelmayer also got the same idea of stock prices following a Normal Distribution.
He started putting the prices in the form a Normal Distribution. To his surprise, he started seeing some kind of informational advantage that the distributions were giving graphically or visually.
If a data set follows a Normal Distribution, it should have: (a) centrality; (b) a measure of dispersion.
The centrality can be in the form of an average. This can be a mean, or a median or a mode.
The distribution or dispersion of each data point should be measured with some dispersion, or a measure of dispersion. There are many measures, such as range, absolute deviation and standard deviation.
However, for Market Profile, we will use "mode" as the centre/average and "standard deviation" as the measure of dispersion.
Properties of a Normal Distribution
About 68% of the data lies within 1 standard deviation (SD) of the average (mode), that is, between −1SD and +1SD.
About 95% of the data lies within 2 SDs of the average, that is between −2SD and +2SD.
Almost all of the data lie between −3SD and +3SD standard from the average.
The graph shows 100% of the observations lie between −3SD and +3SD, but more accurately this is 99.74%.