kelly_monte_carlo: Monte-Carlo optimization of expected log

In shill1729/KellyCriterion: Log-optimal stock allocation

Description

A Monte-Carlo implementation of the Kelly criterion for a continuous return RV.

Usage

kelly_monte_carlo(distr, rate, lb, ub, n = 50000, ...)

Arguments

distr	string for distribution name of "r, p, d" family for simulating, CDFs, and PDFs
rate	the discounting rate
lb	the lower bound for interval given to the uniroot bisection solver
ub	the upper bound for interval given to the uniroot bisection solver
n	the number of samples to use in the Monte-Carlo approximation
...	parameters of distribution, specifically the rdistr(n, params...) form

Details

Using Leibniz's rule one can differentiate under the expectation and then set this expectation to zero. Using LLN we approximate this numerically

Value

list

shill1729/KellyCriterion documentation built on Oct. 12, 2020, 4:21 a.m.