Sequential optimizing strategy in multi-dimensional bounded forecasting games

Details Sequential optimizing strategy in multi-dimensional bounded forecasting games Sequential optimizing strategy in multi-dimensional bounded forecasting games

2009-11-19

arxiv.org/abs/0911.3933v1

Stochastic Processes and their Applications, vol.121, 155-183, 2011

Mathematics

Probability

Scientific paper

We propose a sequential optimizing betting strategy in the multi-dimensional bounded forecasting game in the framework of game-theoretic probability of Shafer and Vovk (2001). By studying the asymptotic behavior of its capital process, we prove a generalization of the strong law of large numbers, where the convergence rate of the sample mean vector depends on the growth rate of the quadratic variation process. The growth rate of the quadratic variation process may be slower than the number of rounds or may even be zero. We also introduce an information criterion for selecting efficient betting items. These results are then applied to multiple asset trading strategies in discrete-time and continuous-time games. In the case of continuous-time game we present a measure of the jaggedness of a vector-valued continuous process. Our results are examined by several numerical examples.

Affiliated with

Also associated with

No associations

Rating

Sequential optimizing strategy in multi-dimensional bounded forecasting games does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Sequential optimizing strategy in multi-dimensional bounded forecasting games, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Sequential optimizing strategy in multi-dimensional bounded forecasting games will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-431525