Other than Kelly (or fractional derivatives), are there other money management strategies in wide use among quant funds? Certainly Kelly is mathematically optimal, but perhaps there are other approaches that take into account factors beyond optimized return (lower risk, less exposure to X, etc.)?
In statistical arbitrage, quant traders attempt to build a neutral portfolio by balancing various assets against each other. Each asset's size within the portfolio isn't determine necessarily by how much money it's expected to generate, but by how correlated it is against other assets.
A simple approach is sector neutrality, in which sector/industry affiliation is the sole criteria for "correlation". A better approach is risk neutrality, in which a risk model that describes each asset's exposure to common factors is fed into a portfolio optimizer. In either case, the goal is to build a portfolio where the assets balance each other.
Neutrality is just a goal, though. There are other issues that may prevent a trader from obtaining the ideal positions, such as position limits, volume limits, inability to get the locates on a short sell, transaction costs, etc. The trading engine must consider these issues as well.
Van Tharp, in his book Definitive Guide to Position Sizing, identifies 31 separate models for money management. In said book he specifically warns against using both the Kelly Criterion and Optimal f.
In addition to the models identified by Van Tharp there is Ralph Vince's Leverage Space Portfolio Model.