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  2. Martingale (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Martingale_(probability...

    In probability theory, a martingale is a sequence of random variables (i.e., a stochastic process) for which, at a particular time, the conditional expectation of the next value in the sequence is equal to the present value, regardless of all prior values. Stopped Brownian motion is an example of a martingale. It can model an even coin-toss ...

  3. Martingale difference sequence - Wikipedia

    en.wikipedia.org/wiki/Martingale_difference_sequence

    By construction, this implies that if is a martingale, then = will be an MDS—hence the name. The MDS is an extremely useful construct in modern probability theory because it implies much milder restrictions on the memory of the sequence than independence , yet most limit theorems that hold for an independent sequence will also hold for an MDS.

  4. Doob's martingale convergence theorems - Wikipedia

    en.wikipedia.org/wiki/Doob's_martingale...

    Then is a stopping time with respect to the martingale (), so () is also a martingale, referred to as a stopped martingale. In particular, ( Y n ) n ∈ N {\displaystyle (Y_{n})_{n\in \mathbf {N} }} is a supermartingale which is bounded below, so by the martingale convergence theorem it converges pointwise almost surely to a random variable Y ...

  5. Doob martingale - Wikipedia

    en.wikipedia.org/wiki/Doob_martingale

    In the mathematical theory of probability, a Doob martingale (named after Joseph L. Doob, [1] also known as a Levy martingale) is a stochastic process that approximates a given random variable and has the martingale property with respect to the given filtration. It may be thought of as the evolving sequence of best approximations to the random ...

  6. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    When X n converges in r-th mean to X for r = 2, we say that X n converges in mean square (or in quadratic mean) to X. Convergence in the r-th mean, for r ≥ 1, implies convergence in probability (by Markov's inequality). Furthermore, if r > s ≥ 1, convergence in r-th mean implies convergence in s-th mean. Hence, convergence in mean square ...

  7. Quadratic variation - Wikipedia

    en.wikipedia.org/wiki/Quadratic_variation

    It can be shown that the quadratic variation [] of a general locally square integrable martingale is the unique right-continuous and increasing process starting at zero, with jumps [] = and such that [] is a local martingale.

  8. Elon Musk and Sam Altman spar over Trump's Stargate AI ...

    www.aol.com/news/musk-altman-trade-barbs-social...

    A war of words between Elon Musk and Sam Altman escalated on social media Thursday, as two of the most powerful men in tech sparred over their rival artificial intelligence initiatives.

  9. Martingale representation theorem - Wikipedia

    en.wikipedia.org/wiki/Martingale_representation...

    The martingale representation theorem can be used to establish the existence of a hedging strategy. Suppose that ( M t ) 0 ≤ t < ∞ {\displaystyle \left(M_{t}\right)_{0\leq t<\infty }} is a Q-martingale process, whose volatility σ t {\displaystyle \sigma _{t}} is always non-zero.