Optimal prediction pools

Socially Optimal Mining Pools

Mining for Bitcoins is a high-risk high-reward activity. Miners, seeking to reduce their variance and earn steadier rewards, collaborate in so-called pooling strategies where they jointly mine for Bitcoins. Whenever some pool participant is successful, the earned rewards are appropriately split among all pool participants. Currently a dozen of different pooling strategies (i.e., methods for dis...

Optimal liquidation in dark pools

We consider a large trader seeking to liquidate a portfolio using both a transparent trading venue and a dark pool. Our model captures the price impact of trading in transparent traditional venues as well as the execution uncertainty of trading in a dark pool. The unique optimal execution strategy uses both venues continuously. The order size in the dark pool can overor underrepresent the portf...

The Optimal Development of Resource Pools

Optimal Strategies for Sports Betting Pools

Every fall, millions of Americans enter betting pools to pick winners of the weekly NFL football games. In the spring, NCAA tournament basketball pools are even more popular. In both cases, teams that are popularly perceived as “favorites” gain a disproportionate share of entries. In large pools there can be a significant advantage to picking upsets that differentiate your picks from the crowd....

Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools

We introduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECT is able to rapidly choose small, nonredundant feature sets from pools containing hundreds of thousands of potentially useful features. It does this by building a decision tree, using features from the pool, that classifies a set of trainin...