Optimal Properties of Exponentially Weighted Forecasts
ABSTRACT The exponentially weighted average can be interpreted as the expected value of a time series made up of two kinds of random components: one lasting a single time period (transitory) and the other lasting through all subsequent periods (permanent). Such a time series may, therefore, be regarded as a random walk with “noise” superimposed. It is also shown that, for this series, the best forecast for the time period immediately ahead is the best forecast for any future time period, because both give estimates of the permanent component. The estimate of the permanent component is imperfect, and so the estimate of a regression coefficient is inconsistent in a relation involving the permanent (e.g. consumption as a function of permanent income). Its bias is small, however.
SourceAvailable from: Oliver Linton[Show abstract] [Hide abstract]
ABSTRACT: We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form E¢ cient Market Hypothesis). We do not impose the no leverage assumption of Lo and MacKinlay (1988) but our asymptotic standard errors are relatively simple and in particular do not require the selection of a bandwidth parameter. We extend the framework to allow for a time varying risk premium through common systematic factors. We show the limiting behaviour of the statistic under a multivariate fads model and under a moderately explosive bubble process: these alternative hypotheses give opposite predictions with regards to the long run value of the statistics. We apply the methodology to …ve weekly size-sorted CRSP portfolio returns from 1962 to 2013 in three subperiods. We …nd evidence of a reduction of linear predictability in the most recent We thank 1 period, for small and medium cap stocks. The main …ndings are not substantially a¤ected by allowing for a common factor time varying risk premium.Do be do be do; 04/2015
Conference Paper: Bullwhip behavior in the Order-Up-To policy with ARIMA demand[Show abstract] [Hide abstract]
ABSTRACT: This paper analyses the bullwhip effect produced by the Order-Up-To (OUT) policy for ARIMA demand processes. Areas in the parametrical space are identified where a bullwhip effect increases or decreases as function of the lead time. In remaining areas the bullwhip effect might be increasing, decreasing or fluctuating, depending upon the parameter values of the demand process.4th World Production and Operations Management Conference, Amsterdam, The Netherlads; 05/2012
Limnology and Oceanography 01/1996; 41(6):1220-1241. DOI:10.4319/lo.19184.108.40.2060 · 3.62 Impact Factor