Neglectedness

Updated
/*
Describe your code here
*/

// Sample two field sizes from a distribution
a = truncate(1 to 1000, .1, 10000) // Lognormal, with extreme values cut off
b = truncate(1 to 1000, .1, 10000)

// Ratio between size of two randomly chosen fields
ratio = max(a/b, b/a)
Updated
/*
Describe your code here
*/

rho1 = uniform(0,1)
rho2 = normal(0.5, 0.25)
rho3 = 2*beta(1,3)

rho = mx(rho1,rho2,rho3,[1,1,1]) // unweighted mixture of the above
Updated
/*
Exploring Isoelastic Utility Functions (IUF) under semi-efficient market conditions
*/

// What if we are uncertain about Rho and model it as lognormally distributed?
// This could be justifiable if we think that 100% efficient markets are impossible to achieve, and log(rho) is normally distributed

rho_lognormal = 0.1 to 1

// vmf is value of marginal funding. It is the gradient of the IUF, x^-rho.
Updated
/*
Exploring Isoelastic Utility Functions (IUF) under semi-efficient market conditions
*/

// CURRENTLY THIS IS MOSTLY A COPY OF THE EFFICIENT MARKET MODEL

// What if we are uncertain about Rho and model it as lognormally distributed?
// This could be justifiable if we think that 100% efficient markets are impossible to achieve, and log(rho) is normally distributed

rho_lognormal = 1 - (0.1 to 1)
Updated
/*
Describe your code here
*/

// For Isoelastic Utility Functions (IUFs), 'compounding' fields have increasing returns, so rho < 0.
// Diminishing returns means rho > 1

// We want to know whether modelling rho as a distribution is comparable (in terms of central values) to
// using a discounted point-estimate rho instead.