capitalist, I think that we will be even more confused with the numbers, there's always a way to get specific set of numbers. The problem is, you won't know if it is applicable to any set of numbers. I've said in the beginning It is very difficult ...

Optimized Risk vs Reward Equation

hmm, z is not the price but the stop loss. Oh well, back to the drawing board. But this is encouraging. If I interpreted everything correctly, these are the rules: - for every price of the first position (for example 105,28; 1,0716; 0.9245...) there ...

Optimized Risk vs Reward Equation

So, if I'm right, the price is the distance from domain of the function to the surface (in our case, the distance to the surface that has saddle point). image image

Optimized Risk vs Reward Equation

Here's the ultra detailed explanation of how to draw a graph of two variable function. Calculus: How to sketch functions of two variables. Chris Tisdell UNSW Sydney video

Optimized Risk vs Reward Equation

I have another question, are the variables mutually exponentially proportional ? Meaning: A variable y is exponentially proportional to a variable x, if y is directly proportional to the exponential function of x, that is if there exists a non-zero ...

Optimized Risk vs Reward Equation

Twoblink, let me see If I got this right: I'm using price as my z-axis, price as a function of stop-loss and lot size. so the coordinates in 3D are (x,y, f(x,y)) and we are looking for f(x,y), the function that gives us optimal price for our stop ...

Optimized Risk vs Reward Equation

I'm not the author, found it amongst various sw pictures. Should be observed on a daily basis when you are on a demo, with bad results and thinking about going live. image

Trading Posters

This Mathematica program could be useful as a starting point in our function finding problem. Many famous sequences occur as the coefficients of a series for an exponential function, which is called the exponential generating function of the ...

Optimized Risk vs Reward Equation

Optimization Problems with Functions of Two Variables url The third example looks similar to our problem, I'll have to solve it a few times to better understand it. Several optimization problems are solved and detailed solutions are presented. ...

Optimized Risk vs Reward Equation

hmm, the optimal function must have boundaries, logarithmic one as lower and exponential one as higher. In computer science, an algorithm is said to be asymptotically optimal if, roughly speaking, for large inputs it performs at worst a constant ...

Optimized Risk vs Reward Equation

Functions of multiple variables can be differentiated with respect to either of their variables, the other variable being understood to be held constant during the differentiation. The partial derivatives are written as ∂f/∂x, ∂f/∂y, and so on. The ...

Optimized Risk vs Reward Equation

Khinchin's Constant In number theory, Aleksandr Yakovlevich Khinchin proved that for almost all real numbers x, the infinitely many denominators ai of the continued fraction expansion of x have an astonishing property: their geometric mean is a ...

Optimized Risk vs Reward Equation

Definition of graph of function of two variables: Suppose that f is a function of x and y. The graph of f consists of all points in space of the form (x,y,f(x,y)) where (x,y) is in the domain of f. A function f of two variables is a relation that ...

Optimized Risk vs Reward Equation

It's like a formula for circumference or area of a circle, it is always 2*r*pi and r^2*pi regardless of the size of the circle. I've been looking at this from a wrong perspective. The positions are related to one another like sphere in a sphere, or ...

Optimized Risk vs Reward Equation

And in the end, second derivative grapher, function grapher and Riemann sum grapher But, start with the first chapter of this on-line course and work your way to derivatives, integrals etc... Then read the thread again and give some fresh ideas ...

Optimized Risk vs Reward Equation

here's some more excel sheets about derivatives, slopes, graphs, etc... to visualize our discussion.

Optimized Risk vs Reward Equation

The interest is there, but the problem is hard, or should I say: The spirit is willing but the flesh is weak. I've mentioned the resemblance to the Fermat's Last Theorem before, the problem looks easy on the surface, but dig a little deeper and ...

Optimized Risk vs Reward Equation

lot size/length diagram first series: lot size (how much you invest): x1, x2, x3....xn second series: length (entry points): y1, y2, y3...yn - the series is convergent if and only if it has a limit, if the series does not have a limit, it is ...

Optimized Risk vs Reward Equation

It took him 2 years to figure out the equation. I hope I will be able to replicate the result in less amount of time. As more people try to figure it out, the less time it will take them to achieve that. How hard can it be? We know a lot of ...

Optimized Risk vs Reward Equation

no, I do not hedge. (but I do use Jacko's antihedge strategy when I'm completely wrong about my first position - situation when it activates and then goes back and hits the stoploss) I also observe all pairs as separate markets. Twoblink gave hints ...

Optimized Risk vs Reward Equation