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In probability theory, the g-expectation is a nonlinear expectation based on a backwards stochastic differential equation (BSDE) originally developed by Shige Peng. == Definition == Given a probability space with is a (''d''-dimensional) Wiener process (on that space). Given the filtration generated by , i.e. , let be measurable. Consider the BSDE given by: : Then the g-expectation for is given by . Note that if is an ''m''-dimensional vector, then (for each time ) is an ''m''-dimensional vector and is an matrix. In fact the conditional expectation is given by and much like the formal definition for conditional expectation it follows that for any (and the function is the indicator function).〔 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「G-expectation」の詳細全文を読む スポンサード リンク
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