Provides a foundation for probability based on game theory rather than measure theory.

• A strong philosophical approach with practical applications.
• Presents in-depth coverage of classical probability theory as well as new theory.

  Table of Contents

  	Preface
  1	Probability and Finance as a Game	1
  Pt. I	Probability without Measure	27
  2	The Historical Context	29
  3	The Bounded Strong Law of Large Numbers	61
  4	Kolmogorov's Strong Law of Large Numbers	75
  5	The Law of the Iterated Logarithm	99
  6	The Weak Laws	121
  7	Lindeberg's Theorem	147
  8	The Generality of Probability Games	167
  Pt. II	Finance without Probability	199
  9	Game-Theoretic Probability in Finance	201
  10	Games for Pricing Options in Discrete Time	237
  11	Games for Pricing Options in Continuous Time	271
  12	The Generality of Game-Theoretic Pricing	293
  13	Games for American Options	317
  14	Games for Diffusion Processes	335
  15	The Game-Theoretic Efficient-Market Hypothesis	351
  	References	375
  	Photograph Credits	399
  	Notation	403
  	Index	405