The basic problem of economics is to take a given set of assets, skills and preferences for a group and organize the optimal activities according to some preference aggregation function. The field of finance is responsible for designing tools to help in this process. Money is an early tool. You assign a weight to every input and potential output, and ask each member of the group to do a one-dimensional linear local optimization. You shower all good things on the members who do this well, and grind the ones who do it badly into misery. The results of these local optimizations feed back into the weight assignments which makes the process high dimension and nonlinear, even though individuals only have to solve univariate linear problems. The approach works well when things are smooth and there a unique global optimum, but if not it can be unstable or get stuck in unpleasant local optimums. Central planning is a tempting approach to mathematical modelers because in principle it can solve the global multidimensional nonlinear problem. It allows the organization of activity to be solved independently of the distribution of outputs, less showering, less misery. It has a reputation for failure, but perhaps with recent advances in applied mathematics combined with more powerful computers it could now outperform money. The game of poker is another approach and I will argue it was responsible for more economic progress in the 19th century than the money economy and that it has popped up in interesting ways at key points of the 20th century. Derivatives trading, which evolved from poker games, is another approach. Rather than have lots of people solve low-dimensional linear local problems, it asks a small group of people to solve higher dimensional nonlinear global problems. The feedback loop is multidimensional and also higher frequency than with money. Showering of good things and misery are still allocated according to optimization skills, and in an exaggerated manner, but only for the trading group. I will discuss the pros and cons of these approaches from the standpoint of mathematical programming (i.e. considerations of social justice, human happiness and morality were reserved for post-talk drinks).