Abstract
The forecasting performance of the Livingston survey and traditional prediction models of stock prices is analysed. The survey forecasts look similar to those from a ‘too large’ prediction model: poor out-of-sample performance and too sensitive to recent and irrelevant information.
Notes
1The data of the Livingston survey are from the Federal Reserve Bank of Philadelphia (http://www.phil.frb.org/). The monthly S&P 500 and S&P Industrials price indices are from S&P's Trade and Securities Statistics (1976), Compustat and DataStream. The dividends on the S&P 500 and the inflation rate are from Shiller's (Citation2000) homepage (http://www.econ.yale.edu/%7Eshiller/data.htm). For a discussion of the historical S&P series, see Jones and Wilson (Citation2002). The 3-month T-bill rate is from FRED II (http://www.research.stlouisfed.org/fred2/).
2Strictly speaking, we would like to have survey data on the expected capital gain ϵ t – 12 (Pt /Pt – 6), but the survey only contains information on expected index levels. Therefore, ϵ t – 12 Pt /ϵ t – 12 Pt − 6 is used as an approximation.
3The ‘out-of-sample R
2’ is , where s is the first period with an out-of-sample forecast, rt
the actual value in t,
the model forecast of the value in t and
the recursively estimated average value.
4Other nonlinear restrictions, for instance, using the max. of the prediction and the negative of the recent dividend yield, give similar results.
5In contrast, Dokko and Edelstein (Citation1989) found that the survey was unbiased in the subsample 1955 to 1985.
6 There is good theoretical and empirical evidence that combining (averaging) forecasts typically reduces the forecast error variance (see, for instance, Bates and Granger, Citation1969).
7Bacchetta et al. (Citation2008) also found a negative correlation between survey expectations and the dividend yield (using the UBS/Gallup poll 1998 to 2003), but a positive correlation with an interest rate.