On the applicability of the Kelly criterion to Engineering Economics

Kelly's Criterion in Portfolio Optimization: A Decoupled Problem

“…One would reasonably expect that the solver will produce solutions that place a large fraction of investment capital in the 10 th stock for any value of risk parameter. Previous work in this area has shown that the unconstrained optimal solution for a single asset is 𝐹 = 𝜇 𝜎 2 in both the discrete (Thorpe 1997;Kim 2008;Vince 2011) and continuous cases (Browne and Whitt 1996). The initial solution is generated such that the solver can reach this intuitive solution and avoid premature convergence.…”

“…This requires that the probability of total loss of investment in an asset be nonzero over the entire course of the investment horizon. If this condition is not met, the Kelly Criterion may return optimum 𝑓 𝑖 values that are greater than 1 (Rotando and Thorpe 1997;Kim 2008;Vince 2011). A specific example was shown by Rotando and Thorpe (1997); they considered a truncated normal distribution for returns on the S&P index, i.e.…”

“…These ideas were later embraced by gamblers and were used to maximize the winnings one would expect to see from a large number of bets with well-defined probabilities. A gambler that bets a critical fraction of their wealth per bet can expect to see an average rate of return per bet that maximizes their total return over time (Rotando and Thorpe 1992;Browne and Whitt 1996;Thorpe 1997;Nekrasov 2014;Kim 2008;Vince 2011). In its simplest form, where the outcome of each bet was considered binary with well-defined odds and probabilities, and successive bets are mutually independent, Kelly's result is a simple formula for the critical fraction of wealth that will maximize a gambler's average return over a large number of bets (Rotando and Thorpe 1992;Browne and Whitt 1996;Thorpe 1997;Vince 2011;Nekrasov 2014).…”

“…Kelly's Criterion is well known among gamblers as a betting strategy (Rotando and Thorpe 1992;Browne and Whitt 1996;Thorpe 1997). Kelly's result is, in its simplest sense, a solution to an optimization problem which maximizes logarithmic utility and was originally applied to a technical problem in information theory (Kelly 1956;Kim 2008). The Kelly Criterion has been discussed in contexts outside of gambling, for example, in engineering economics (Kim 2008).…”

“…Kelly's result is, in its simplest sense, a solution to an optimization problem which maximizes logarithmic utility and was originally applied to a technical problem in information theory (Kelly 1956;Kim 2008). The Kelly Criterion has been discussed in contexts outside of gambling, for example, in engineering economics (Kim 2008). These ideas were later embraced by gamblers and were used to maximize the winnings one would expect to see from a large number of bets with well-defined probabilities.…”