6 months TopStep 50K Net Profits
- Thread starter Sekiyo
- Start date
It’s said speculation is about successful anticipation of price movement.
I’d say it’s more about accurate assessment of potential price movements.
Anyway .. in both cases it’s about acquaintance.
You can outguess your close friends and family or anything familiar to you.
It’s all about observations and interactions.
The more time you’ve spent communicating with the object, the more you can assess its potential.
If a friend sends you a noisy message,
Then you should be able to fill in the blank.
Because you have past and situational knowledge.
But if a stranger sends you the same message,
Then the numbers of possibilities are greater,
Filling the blanks becomes way harder.
It’s about narrowing down propensities.
Reducing the entropy btw you and the market.
I’d say it’s more about accurate assessment of potential price movements.
Anyway .. in both cases it’s about acquaintance.
You can outguess your close friends and family or anything familiar to you.
It’s all about observations and interactions.
The more time you’ve spent communicating with the object, the more you can assess its potential.
If a friend sends you a noisy message,
Then you should be able to fill in the blank.
Because you have past and situational knowledge.
But if a stranger sends you the same message,
Then the numbers of possibilities are greater,
Filling the blanks becomes way harder.
It’s about narrowing down propensities.
Reducing the entropy btw you and the market.
How do you narrow down possibilities ?
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the "amount of information" (in units such as shannons, commonly called bits) obtained about one random variable through observing the other random variable
In plain English: x knowing P
P is prior information or base rate.
Priors aren’t always useful, no dependence.
Knowing that I am French, male and rafiné tells you nothing about my trading faculties.
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the "amount of information" (in units such as shannons, commonly called bits) obtained about one random variable through observing the other random variable
In plain English: x knowing P
P is prior information or base rate.
Priors aren’t always useful, no dependence.
Knowing that I am French, male and rafiné tells you nothing about my trading faculties.
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