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Its quadratic variation is the process, written as , defined as. where ranges over partitions of the interval and the norm of the partition is the mesh. This limit, if it exists, is defined using convergence in probability. Note that a process may be of finite quadratic variation in the sense of the definition given here and its paths be ...
An alternative characterisation of the Wiener process is the so-called Lévy characterisation that says that the Wiener process is an almost surely continuous martingale with W 0 = 0 and quadratic variation [W t, W t] = t (which means that W t 2 − t is also a martingale).
Itô calculus, named after Kiyosi Itô, extends the methods of calculus to stochastic processes such as Brownian motion (see Wiener process). It has important applications in mathematical finance and stochastic differential equations. The central concept is the Itô stochastic integral, a stochastic generalization of the Riemann–Stieltjes ...
The density transformation from P to Q is given by the Girsanov theorem. In probability theory, the Girsanov theorem tells how stochastic processes change under changes in measure. The theorem is especially important in the theory of financial mathematics as it tells how to convert from the physical measure, which describes the probability that ...
Quadratic variation is defined as a limit as the partition gets finer, whereas p-variation is a supremum over all partitions. Thus the quadratic variation of a process could be smaller than its 2-variation. If W t is a standard Brownian motion on [0, T], then with probability one its p-variation is infinite for and finite otherwise. The ...
Every finite-variation semimartingale is a quadratic pure-jump semimartingale. An adapted continuous process is a quadratic pure-jump semimartingale if and only if it is of finite variation. For every semimartingale X there is a unique continuous local martingale starting at zero such that is a quadratic pure-jump semimartingale (He, Wang & Yan ...
Calculus of variations is concerned with variations of functionals, which are small changes in the functional's value due to small changes in the function that is its argument. The first variation [l] is defined as the linear part of the change in the functional, and the second variation [m] is defined as the quadratic part. [22]
The Stratonovich integral or Fisk–Stratonovich integral of a semimartingale against another semimartingale Y can be defined in terms of the Itô integral as := + [,], where [X, Y] t c denotes the optional quadratic covariation of the continuous parts of X and Y, which is the optional quadratic covariation minus the jumps of the processes and , i.e.