You need High, Low, Close data to chart the stochastic.
It is a momentum indicator that compares a security's closing price to its price range over a given time period. The oscillator's sensitivity to market movements can be reduced by adjusting the time period or by taking a moving average of the result. This indicator is calculated with the following formula:
%K = 100[(C - L14)/(H14 - L14)]
C = the most recent closing price
L14 = the low of the 14 previous trading sessions
H14 = the highest price traded during the same 14-day period.
%D = 3-period moving average of %K
The theory behind this indicator is that in an upward-trending market, prices tend to close near their high, and during a downward-trending market, prices tend to close near their low. Transaction signals occur when the %K crosses through a three-period moving average called the "%D".
Also, stochastics is at the heart of the insurance industry.
2006-10-12 20:59:21
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answer #1
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answered by dredude52 6
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A stochastic process is a sequence of measurable functions, that is, a random variable X defined on a probability space (Ω, Pr) with values in a space of functions F. The space F in turn consists of functions I â D. Thus a stochastic process can also be regarded as an indexed collection of random variables {Xi}, where the index i ranges through an index set I, defined on the probability space (Ω, Pr) and taking values on the same codomain D (often the real numbers R). This view of a stochastic process as an indexed collection of random variables is the most common one.
A notable special case is where the index set is a discrete set I, often the nonnegative integers {0, 1, 2, 3, ...}.
In a continuous stochastic process the index set is continuous (usually space or time), resulting in an uncountably infinite number of random variables.
Each point in the sample space Ω corresponds to a particular value for each of the random variables and the resulting function (mapping a point in the index set to the value of the random variable attached to it) is known as a realisation of the stochastic process. In the case the index family is a real (finite or infinite) interval, the resulting function is called a sample path.
A particular stochastic process is determined by specifying the joint probability distributions of the various random variables.
Stochastic processes may be defined in higher dimensions by attaching a multivariate random variable to each point in the index set, which is equivalent to using a multidimensional index set. Indeed a multivariate random variable can itself be viewed as a stochastic process with index set {1, ..., n}.
2006-10-13 04:02:46
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answer #2
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answered by Anonymous
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go to 3 of the best website:
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you will learn how stochastic chart
2006-10-13 02:15:55
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answer #3
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answered by Hoa N 6
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2006-10-13 12:01:40
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answer #4
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answered by stock.geek 2
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It is used in technical analysis. It is a momentum indicator.
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2006-10-13 06:30:05
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answer #5
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answered by Anonymous
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