Unbiased predictor

Unbiased predictor

A theory that spot prices at some future date will be equal to today's forward rates.

Unbiased Expectations Hypothesis

In foreign exchange, a theory that forward exchange rates for delivery at some future date are equal to the spot rates for that date. The hypothesis only functions in the absence of a risk premium. Critics contend that the unbiased expectations evidence shows that unbiased expectations do not occur in actual trading. It is also called an unbiased predictor.
References in periodicals archive ?
Provided the movement of teachers in and out of a grade has not changed the makeup of students enrolled in that grade, this finding supports the conclusion that measured value-added of teachers is an unbiased predictor of future test-score gains, as there appears to be no other explanation for the resulting improvement in test scores.
This paper uses cointegration techniques to test the hypothesis that the forward rate for the Greek drachma-US dollar exchange rate is an unbiased predictor of the future spot rate.
The Theoretical Price as an Unbiased Predictor of True Prices
Kohlhagen (1975) found that, in most cases, the forward is an unbiased predictor of the realized spot.
If the rate of change in the arithmetic mean is an unbiased predictor of the rate of change in the geometric mean, then the intercept should be zero, the slope coefficient should be one, and the error should be a random disturbance.
Also, the best linear unbiased predictor (BLUP) of the P-Gr value of each [S.sub.1] family was calculated.
The earlier works tended to conclude that the forward exchange rate is an unbiased predictor of the future spot rate, albeit not an accurate one in the sense that it does not exhibit minimum forecast error.
Abbreviations: BLUP, best linear unbiased predictor; GDD, growing degree days; GFD, grain-filling duration; G x Y x N x P, genotype year x nitrogen x phosphorous; HED, vegetative duration; HI, harvest index; KPS, kernels per spike; KW, kernel weight; MHT, mature plant height; SPK, spikes per square meter; STR, straw yield; VHT, vegetative shoot height; YLD, grain yield.
He explains the need for more than one random-effect term when fitting a regression line and in a designed experiment; the evaluation of the variances of random-effect terms; interval estimates for fixed-effect terms in mixed models; estimation of random effects in mixed models using Best Linear Unbiased Predictors; more advanced mixed models for more elaborate data sets; the use of mixed models for the analysis of unbalanced experimental designs; extending mixed modeling; and why the criterion for fitting mixed models is called the REsidual Maximum Likelihood (REML).
Dubbed "mixed model equations (MMEs) that produce best linear unbiased predictors," the approach uses a disease-ranking system and matrix information to predict susceptibility of a plant species, based on how genetically similar it is to the targeted weed--Russian thistle, for example.
Corporate practitioner Galwey writes for senior undergraduates, postgraduate students and professionals, starting by explaining the need for more than one random-effect term when fitting a regression line or when designing an experiment, estimation of the variances of random-effect terms, interval estimates for fixed-effect terms in mixed models, best linear unbiased predictors in the estimation of random effects in mixed models, advanced mixed models for more elaborate data sets, the use of mixed models for the analysis of unbalanced experimental designed, going beyond mixed modeling and the reasons why the criterion for fitting mixed models is called the residual maximum likelihood.