Abstract
Using a simple dividend model, we illustrate and synthesize the sources of stock market mispricing and excess volatility based upon two hypotheses—inflation illusion and heterogeneous beliefs. Our theoretical framework posits that equity mispricing arises when investors have subjective expectations about discount rates or dividend growth rates. We then analyze the sources of equity mispricing and market excess volatility under a VAR framework. Empirically, we find that both inflation illusion and heterogeneous beliefs explain equity mispricing. However, heterogeneous beliefs play a more important role in explaining stock mispricing in the long run. We also find that heterogeneous beliefs cause excess volatility, but inflation illusion does not. Therefore, dispersion in investors’ beliefs is a better explanation of stock market mispricing than the investors’ inability to properly discount future cash flows.
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Notes
Inflation is exponentially smoothed using 12 monthly lags. Excess log dividend growth rates are the realized log dividend growth rate minus 3-month log T-bill rates. Excess returns are calculated in the same manner.
Many other proxies have been proposed. For example, Graham and Harvey (1996) use the dispersion among newsletter "forecasts"; Bessembinder et al. (1996) employ the open interest on the Standard & Poor's (S&P) 500 Index futures; and Scheinkman and Xiong (2003) and Chen et al. (2009a) use trading volume.
We drop the component stocks with less than three earnings estimates for the corresponding quarter. For a robust check, we also use the range of financial analyst estimates and find the results are qualitatively the same.
The detailed statistics are upon request.
We use the data from 1974 because the I/B/E/S data is available from 1974.
Similar to Brunnermeier and Julliard (2008), we use Bayesian regression for the tests.
Follow Campbell and Vuolteenaho (2004), we employ one lag in the VAR model.
Alternatively, we also incorporate risk measures (i.e., VIX and default yield spread) into the VAR, the test results are qualitatively similar.
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Appendix
Appendix
We define \( x_{t} \) as a 4 × 1 vector for the four variables at time t, i.e.,Footnote 9
The VAR system with one lag is specified as
where B is a 4 × 4 matrix of VAR coefficients and \( \xi_{t} \) is a 4 × 1 vector representing the shocks to the VAR system. Given (16), the multiperiod forecast is determined as
Define further two vectors, \( e2 = (0,1,0,0)^{'} \) and \( e3 = (0,0,1,0)^{'} \), the discounted expected future excess log dividend growth rates, \(\sum_{\tau = 1}^{\infty } {\rho^{\tau - 1} } \hat{E}_{t} (\Updelta d_{t + \tau }^{e} )\), are, therefore, given by
where \( \hat{E}_{t} \) is the conditional expectations calculated using the estimated VAR parameters. Likewise, the discounted expected future excess log returns, \( \sum\nolimits_{\tau = 1}^{\infty } {\rho^{\tau - 1} } \hat{E}_{t} (r_{t + \tau }^{e} ), \) are given by
With the estimated VAR parameters, we can decompose the realized, demeaned log price-dividend ratio, \( \tilde{p}_{t} - \tilde{d}_{t} \), into three components: (a) the discounted expected excess log dividend growth rates, \( \sum_{\tau = 1}^{\infty } {\rho^{\tau - 1} } \hat{E}_{t} \left( {\Updelta d_{t + \tau }^{e} } \right); \) (b) the discounted expected excess log stock returns, \( \sum_{\tau = 1}^{\infty } {\rho^{\tau - 1} } \hat{E}_{t} \left( {r_{t + \tau }^{e} } \right); \) and (c) the mispricing term, \( \tilde{\varepsilon }_{t} \), as follows,
The demeaned fundamental component, \( p_{t} - d_{t} \), consists of the first two terms in the right-hand side of (A6), whereas the mispricing term, \( \tilde{\varepsilon }_{t} \), is the difference between the realized price-dividend ratio, \( \tilde{p}_{t} - \tilde{d}_{t} \), and the fundamental component, \( p_{t} - d_{t} \).
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Chen, C.R., Lung, P.P. & Wang, F.A. Where are the sources of stock market mispricing and excess volatility?. Rev Quant Finan Acc 41, 631–650 (2013). https://doi.org/10.1007/s11156-012-0326-8
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DOI: https://doi.org/10.1007/s11156-012-0326-8