What drives stock price movements?
We discuss the relative importance of cash flow news versus discount rate news, in explaining the volatility of aggregate stock returns
Consider the following formula for the price of a stock:
where D represents dividends and ICC is the cost of equity. The formula says that the price of a stock is determined by a potentially infinite stream of future dividends D discounted at a rate ICC. At each point in time, dividends are not known with certainty, hence the term E(D), which shows that dividends are expressed as an expectation based on current information.
Returns over a period j are defined as the change in prices over such period:
The question is: how much are returns driven by a change in E(D) versus a change in ICC? Put it differently, we want to understand how much price changes are driven by news about cash flows versus news about the cost of equity.
how much price changes are driven by news about cash flows versus news about the cost of equity?
A secondary question is: does the length of period j matter in answering the previous question? That is to say whether the relative importance of cash flow news versus news on the cost of equity depends on the horizon over which we measure returns (e.g. 1 quarter, 1 year, 3 years, etc).
To tackle these questions we follow Chen, Da and Zhao (2013). These authors develop a technique to estimate ICC, starting from current stock prices and analysts’ expectations of future cash flows E(D). With the estimations of ICC and E(D) at hand, Chen, Da and Zhao compute the following decomposition for the variance of stock returns, over different time horizons.
In their decomposition, the variance of stock returns is decomposed into variance generated by news on discount rates and news on cash flows. Discount rate (DR) news represent variations in future discount rates (i.e. in ICC), which will be mainly driven by changes in the attitude of investors towards risk (risk premia). More simply, cash flow (CF) news are changes in expected cash flows.
According to the above estimates, CF news explain 36% of the aggregate (e.g. S&P index) stock price variation over one year. This percentage increases to 60% at the three-year horizon. The remaining variation in stock prices is explained by DR news.
CF news explain 36% of the aggregate (e.g. S&P index) stock price variation over one year
Another way to illustrate this result is to plot CF news against stock price returns, as in the figure below. CF news track closely the variation in stock prices, particularly at the two-year horizon.
What do we learn from this evidence?
The evidence above shows that in order to predict aggregate returns one needs to formulate a prediction for both CF and DR news. This is in contrast with the established view (most notably defended by Cochrane in his presidential address at the American Finance Association in 2011, see Cochrane (2011)) that almost all variation in aggregate stock prices comes from variations in discount rates.
To set up a directional strategy on, say, the S&P500 the challenge that one faces is double. We need a model for forecasting the change in CFs, and another one for forecasting the change in risk premia.
References
Bansal, R. and Yaron, A., 2004. Risks for the long run: A potential resolution of asset pricing puzzles. The journal of Finance, 59 (4), pp.1481-1509.
Campbell, J.Y. and Cochrane, J.H., 1999. By force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of political Economy, 107 (2), pp.205-251.
Campbell, J.Y. and Shiller, R.J., 1988. The dividend-price ratio and expectations of future dividends and discount factors. The Review of Financial Studies, 1 (3), pp.195-228.
Chen, L., Da, Z. and Zhao, X., 2013. What drives stock price movements?. The Review of Financial Studies, 26(4), pp.841-876.
Cochrane, J.H., 2011. Presidential address: Discount rates. The Journal of finance, 66(4), pp.1047-1108.
Van Binsbergen, J.H. and Koijen, R.S., 2010. Predictive regressions: A present‐value approach. The Journal of Finance, 65 (4), pp.1439-1471.
Welch, I. and Goyal, A., 2008. A comprehensive look at the empirical performance of equity premium prediction. The Review of Financial Studies, 21 (4), pp.1455-1508.
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