Does the Net Flow of Funds Help to Predict the S&P 500 Index?

Thomas A. Carnes ； Michael Mosebach ； Mohammad Najand

《Advances in Investment Analysis and Portfolio Management》 3期 (2008/11) Pp. 143-156

https://doi.org/10.6291/AIAPM.2008.03.08

並列摘要

Although there is considerable evidence that stock returns are predictable both individually and in aggregate, prior investigations as to whether share prices are significantly affected by demand shocks have mixed results. We extend prior research on this issue by testing the forecasting ability of five univariate and two multivariate models with respect to the S&P 500 Index. We hypothesize that the multivariate dynamic regression and state-space models, which incorporate both previous prices and current equity mutual fund flows, will result in more accurate predictions of future stock prices than univariate models. Our results support our hypothesis both for one-month-ahead and onequarter-ahead predictions.

並列關鍵字

Dynamic Regression ； State Space ； Random Walk ； Exponential Smoothing

參考文獻

Aoki, M. (1987). State space modeling of time series. New York: Springer-Verlag.

Aoki, M., & Havenner, A. M. (1989). A method for approximate representation of vector-valued time series and its relation to two alternatives. Journal of Econometrics, 42, October, 181-199.

Bakshi, S. G., & Chen, Z. (1994). Baby boom, population aging, and capital markets. Journal of Business, 67, April, 165-202.

Beneish, M., & Whaley, R. (1996). An anatomy of the “ S & P game”: The effects of changing the rules. Journal of Finance, 51, December 1909-30.

Cha, H.-J., & Lee, B. S. (2001). The market demand curve for common stocks: Evidence from equity mutual fund flows. Journal of Financial and Quantitative Analysis, 36, June,195-220.