Forecasting and seasonal adjustment
An examination of whether one should seasonally adjust data before developing multivariate time series models to provide forecasts.
AUTHORS: Bagshaw, Michael L.
Institutional investors, analyst following, and the January anomaly
Studies have documented that average stock returns for small, low-stock-price firms are higher in January than for the rest of the year. Two explanations have received a great deal of attention: the tax-loss selling hypothesis and the gamesmanship hypothesis. This paper documents that seasonality in returns is not a phenomenon observed only for small firms' stock or those with low prices. Strong seasonality in excess returns is reported for a sample of widely followed firms. Sample firms have unusually low excess returns in January, and returns adjust upward over the remainder of the year. These results are consistent with the gamesmanship hypothesis but not the tax-loss-selling hypothesis. As financial institutions rebalance their portfolios in January to sell the stock of highly visible and low-risk firms, there is downward price pressure in January. In addition, the results suggest that firm visibility explains why seasonality in returns is related to firm size and stock price. Once we control for visibility, market value and uncertainty do not appear to be important determinants of seasonality.
AUTHORS: Ackert, Lucy F.; Athanassakos, George
A problem of seasonal adjustment
A discussion of how new financial instruments have made accurate seasonal adjustment of monetary data more difficult since 1980.
AUTHORS: Mugel, Richard L.
The problem of seasonally adjusted money
An essay on the effect that seasonal money supply fluctations have on the measurement of M1 and on Federal Reserve money supply management, with a discussion of the X-11 adjustment method and suggestions for improving it.
AUTHORS: Carlson, John B.
AUTHORS: Judd, John P.
Residual seasonality and monetary policy
Much recent discussion has suggested that the official real GDP data are inadequately adjusted for recurring seasonal fluctuations. A similar pattern of insufficient seasonal adjustment also affects the published data for a key measure of price inflation. Still, such residual seasonality in the published output and inflation statistics is unlikely to mislead Federal Reserve policymakers or adversely affect the setting of monetary policy.
AUTHORS: Pyle, Benjamin; Wilson, Daniel J.; Rudebusch, Glenn D.
Estimated variance of seasonally adjusted series
For model-based seasonal adjustment, there are explicit formulas for obtaining the variance of the seasonal factors or the seasonally adjusted series. For series adjusted with X-11 or X-12, variance estimates are generally based on a linear approximation of the seasonal adjustment procedure. The work of Pfeffermann (1992) extends earlier work by Wolter and Monseur. This study uses simulated series and comparisons of alternative seasonal adjustment results for a few economic series to assess the accuracy of variance estimates. Pfeffermann's method gives good results when the true seasonal is centered and follows a fairly smooth evolution from year to year. Comparisons with formula-based computations and estimates from the Tramo-Seats programs by Maravall and Gomez show the latter can give good variance results for series adjusted with X-11 even if the seasonal factors themselves differ from X-11 factors.
AUTHORS: Cleveland, William P.
Inflation, interest rates, and seasonality
AUTHORS: Judd, John P.; Biehl, Andrew R.
AUTHORS: Butler, Larry
Interactions between the seasonal and business cycles in production and inventories
This paper shows that in several U.S. manufacturing industries, the seasonal variability of production and inventories varies with the state of the business cycle. We present a simple model which implies that if firms reduce the seasonal variability of their production as the economy strengthens, and they either hold constant or increase the stock of inventories they bring into the high-production seasons of the year, then they must face upward-sloping and convex marginal production cost curves. We conclude that firms in a number of industries face upward-sloping and convex marginal-production-cost curves.
AUTHORS: Cecchetti, Stephen G.; Kashyap, Anil K.; Wilcox, David W.