Predictive ability of three different estimates of “cay” to excess stock returns - A comparative study South Africa & U.S. -

Emara, Noha (2014): Predictive ability of three different estimates of “cay” to excess stock returns - A comparative study South Africa & U.S. -. Published in: European Research Studies Journal , Vol. 17, No. 1 (2014): pp. 3-17.

Abstract

The results of Lettau and Ludvigson (2001) show that Cay-LL has a significant predictive power both in the in-sample and the out-of-sample forecast of excess return. Our study departs from Lettau and Ludvigson (2001) in adding and comparing other two estimates of cay namely cay-OLS and cay-DLS besides cay-LL for forecasting excess return in both the United States and South Africa. Using quarterly data over the period 1988:1 to 2012:2, the results for the United States suggest that the three alternative measures of cay have positive significant predicting ability for the in-sample and out-of-sample forecasting models. Furthermore, and in line with the results of Lettau and Ludvigson (2001), cay-LL has the least mean squared forecasting errors. For the case of South Africa, lagged excess return and dividend yield beat the three alternative measures of cay in forecasting excess return. The results suggest that for the case of South Africa, the trend deviations of the macroeconomic variables is not a strong predictor of the excess stock returns over a treasury bill rate, and cannot account for a statistical significant variation in future excess returns.

• Item Type: MPRA Paper
• Language: English
• Keywords: Forecast; Excess Return; In-sample; Out-of-sample; Nested Forecast
• Subjects: E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E21 - Consumption ; Saving ; Wealth; G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

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