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Theorem

Girsanov's Theorem

Probability and Statistics

Girsanov's Theorem describes how the drift of a stochastic process changes under a change of the underlying probability measure, showing that a suitable change of measure can remove a process's drift entirely, turning it into driftless Brownian motion under the new measure. Named for Igor Girsanov, it is a foundational tool of stochastic calculus widely used in mathematical finance to switch between real-world and risk-neutral pricing measures.

Facts
Statement
If Yt is a local martingale under P then the process Y tilde t = Yt minus [Y,X]t is a Q local martingale on the filtered probability space Omega, F, Q, F t to the W. 1
Proof Year
1960 1
Classification
Statement Form
Identity or Equation 1
Sources
1. Girsanov theorem, Wikipedia
  • Statement section, formal formulation
    if Y_t is a local martingale under P then the process Y~_t = Y_t minus [Y,X]_t is a Q local martingale on the filtered probability space Omega, F, Q, F^W_t
  • History section
    Results of this type were first proved by Robert Horton Cameron and W. T. Martin in the 1940s and by Igor Girsanov in 1960.
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