Variable

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Variable

An element in a model. For example, in the model RS&Pt+1 = a + b Tbill t + et, where RS&Pt+1 is the return on the S&P in month t+1 and Tbill is the Tbill return at month t, both RS&P and Tbill are "variables" because they change through time; i.e., they are not constant.
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Variable

Anything that does not have a set value. In basic algebra, a variable is often expressed as "x." Variables in economics and finance may be measures such as GDP, prices, or interest rates. Analysts use complicated equations to determine the value of some variables at the present time and even more complicated equations to predict their possible future values. See also: Regression.
Farlex Financial Dictionary. © 2012 Farlex, Inc. All Rights Reserved

variable

Something, such as stock prices, earnings, dividend payments, interest rates, and gross domestic product, that has no fixed quantitative value. See also dependent variable, independent variable.
Wall Street Words: An A to Z Guide to Investment Terms for Today's Investor by David L. Scott. Copyright © 2003 by Houghton Mifflin Company. Published by Houghton Mifflin Company. All rights reserved. All rights reserved.
References in periodicals archive ?
We assume a collection of program variables [f.sub.a] in [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] to denote the fixed points of the recursive definitions of the overloaded functions a.
An ML type environment, TE, is a finite map from program variables to ML type schemes.
The number of shape-nodes associated with a single control-flow-graph vertex can grow to be very large - in the worst case, doubly exponential in the number of program variables (i.e., [2.sup.2[absolute value of PVar]]).
Since both the program variable [D.sub.it] and its interaction [D.sub.it][R.sub.it] may be statistically endogenous, we again employ instrumental variables regressions.
They produced Durbin-Watson statistics of 0.3331 and 0.4952, respectively, which permits weak (10% level of significance) rejection of the null hypothesis of no cointegration between the black-white unemployment rate gap and black prime-time television program variables and a strong rejection (5% level of significance) of the null hypothesis of no cointegration relationship between the black unemployment rate and black prime-time television program variables.
(We define the set of state formulas SF below.) The set of states S is obtained by taking the Cartesian product of domains of all program variables, i.e., given a program with n variables V = {[v.sub.1], [v.sub.2], ..., [V.sub.n]}, each state s [element of] S corresponds to a valuation of all the variables of the program
Versions are traditionally denoted by applying subscripts to the name of the original program variable, so SSA versions of variable v will be denoted [v.sub.1], [v.sub.2], and so forth.
Such benefits of analysis are evaluated not only in terms of accuracy, i.e., the ability to determine the actual dependencies among the program variables, but also of effectiveness, measured in terms of code reduction and also in terms of the ultimate performance of the parallelized programs, i.e., the actual speedup obtainable with respect to the sequential version.
We introduce a second program variable p and propose the invariant I: p [is less than or equal to] q [and] [unkeyable] (i,j: i < p [and] j < q [and] i [is not equal to] j: a[i].Key [is not equal to] a[j].Key) [and] [unkeyable](j: q [is less than or equal to] j: [unkeyable](i: i < p: a[i].Key = a[j].
Relationship of teacher and program variables to beginning agriculture teachers' sense of efficacy.

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