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Stochastic oscillator is a momentum indicator within technical analysis that uses support and resistance levels as an oscillator. George Lane developed this indicator in the late 1950s. [1] The term stochastic refers to the point of a current price in relation to its price range over a period of time. [2]
The word stochastic is used to describe other terms and objects in mathematics. Examples include a stochastic matrix , which describes a stochastic process known as a Markov process , and stochastic calculus, which involves differential equations and integrals based on stochastic processes such as the Wiener process , also called the Brownian ...
The term random function is also used to refer to a stochastic or random process, [25] [26] because a stochastic process can also be interpreted as a random element in a function space. [27] [28] The terms stochastic process and random process are used interchangeably, often with no specific mathematical space for the set that indexes the ...
This can be used to show that the gambler's total gain or loss varies roughly between plus or minus the square root of the number of games of coin flipping played. de Moivre's martingale: Suppose the coin toss outcomes are unfair, i.e., biased, with probability p of coming up heads and probability q = 1 − p of tails. Let
Williams used a 10 trading day period and considered values below −80 as oversold and above −20 as overbought. But they were not to be traded directly, instead his rule to buy an oversold was %R reaches −100%. Five trading days pass since −100% was last reached %R rises above −95% or −85%. or conversely to sell an overbought condition
The stochastic oscillator is a momentum indicator used in technical analysis, introduced by George Lane in the 1950s, to compare the closing price of a commodity to its price range over a given time span. Excellent. Clearest explanation that I have seen so far. The stochastic oscillator is based on momentum
Monte Carlo methods are used in corporate finance and mathematical finance to value and analyze (complex) instruments, portfolios and investments by simulating the various sources of uncertainty affecting their value, and then determining the distribution of their value over the range of resultant outcomes.
Suppose that , [,] is given, and we wish to compute .Stochastic computing performs this operation using probability instead of arithmetic. Specifically, suppose that there are two random, independent bit streams called stochastic numbers (i.e. Bernoulli processes), where the probability of a 1 in the first stream is , and the probability in the second stream is .