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86
Predictive regressions
 Journal of Financial Economics
, 1999
"... When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression setting. Bayesian ..."
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Cited by 257 (16 self)
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When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under speci"cations that di!er with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is speci"ed as "xed or stochastic. The posteriors di!er across such speci"cations, and asset allocations in the presence of estimation risk exhibit sensitivity to those
The equity share in new issues and aggregate stock returns
 JOURNAL OF FINANCE
, 2000
"... The share of equity issues in total new equity and debt issues is a strong predictor of U.S. stock market returns between 1928 and 1997. In particular, firms issue relatively more equity than debt just before periods of low market returns. The equity share in new issues has stable predictive power i ..."
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Cited by 152 (25 self)
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The share of equity issues in total new equity and debt issues is a strong predictor of U.S. stock market returns between 1928 and 1997. In particular, firms issue relatively more equity than debt just before periods of low market returns. The equity share in new issues has stable predictive power in both halves of the sample period and after controlling for other known predictors. We do not find support for efficient market explanations of the results. Instead, the fact that the equity share sometimes predicts significantly negative market returns suggests inefficiency and that firms time the market component of their returns when issuing securities.
A Comprehensive Look at the Empirical Performance of Equity Premium Prediction,” working paper
, 2004
"... Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earningsprice ratios, dividend payout ratios, net issuing rati ..."
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Cited by 125 (4 self)
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Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earningsprice ratios, dividend payout ratios, net issuing ratios, bookmarket ratios, interest rates (in various guises), and consumptionbased macroeconomic ratios (cay). The typical paper reports that the variable predicted well in an insample regression, implying forecasting ability. Our paper explores the outofsample performance of these variables, and finds that not a single one would have helped a realworld investor outpredicting the thenprevailing historical equity premium mean. Most would have outright hurt. Therefore, we find that, for all practical purposes, the equity premium has not been predictable, and any belief about whether the stock market is now too high or too low has to be based on theoretical prior, not on the empirically variables we have explored.
Optimal investment, growth options, and security returns
 Journal of Finance
, 1999
"... As a consequence of optimal investment choices, a firm’s assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm’s systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: ~ ..."
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Cited by 116 (5 self)
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As a consequence of optimal investment choices, a firm’s assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm’s systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: ~i! the timeseries relation between the booktomarket ratio and asset returns; ~ii! the crosssectional relation between booktomarket, market value, and return; ~iii! contrarian effects at short horizons; ~iv! momentum effects at longer horizons; and ~v! the inverse relation between interest rates and the market risk premium. RECENT EMPIRICAL RESEARCH IN FINANCE has focused on regularities in the cross section of expected returns that appear anomalous relative to traditional models. Stock returns are related to booktomarket, and market value. 1 Past returns have also been shown to predict relative performance, through the documented success of contrarian and momentum strategies. 2 Existing explanations for these results are that they are due to behavioral biases or risk premia for omitted state variables. 3 These competing explanations are difficult to evaluate without models that explicitly tie the characteristics of interest to risks and risk premia. For example, with respect to booktomarket, Lakonishok et al. ~1994! argue: “The point here is simple: although the returns to the B0M strategy are impressive, B0M is not a ‘clean ’ variable uniquely associated with eco
Investor Sentiment and the CrossSection of Stock Returns
, 2003
"... We examine how investor sentiment affects the crosssection of stock returns. Theory predicts that a broad wave of sentiment will disproportionately affect stocks whose valuations are highly subjective and are difficult to arbitrage. We test this prediction by studying how the crosssection of subse ..."
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Cited by 100 (8 self)
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We examine how investor sentiment affects the crosssection of stock returns. Theory predicts that a broad wave of sentiment will disproportionately affect stocks whose valuations are highly subjective and are difficult to arbitrage. We test this prediction by studying how the crosssection of subsequent stock returns varies with proxies for beginningofperiod investor sentiment. When sentiment is low, subsequent returns are relatively high on smaller stocks, high volatility stocks, unprofitable stocks, nondividendpaying stocks, extremegrowth stocks, and distressed stocks, consistent with an initial underpricing of these stocks. When sentiment is high, on the other hand, these patterns attenuate or fully reverse. The results are consistent with predictions and appear unlikely to reflect an alternative explanation based on compensation for systematic risk.
Stock Return Predictability and Model Uncertainty
, 2002
"... We use Bayesian model averaging to analyze the sample evidence on return predictability in the presence of model uncertainty. The analysis reveals insample and outofsample predictability, and shows that the outofsample performance of the Bayesian approach is superior to that of model selecti ..."
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Cited by 98 (3 self)
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We use Bayesian model averaging to analyze the sample evidence on return predictability in the presence of model uncertainty. The analysis reveals insample and outofsample predictability, and shows that the outofsample performance of the Bayesian approach is superior to that of model selection criteria. We find that term and market premia are robust predictors. Moreover, smallcap value stocks appear more predictable than largecap growth stocks. We also investigate the implications of model uncertainty from investment management perspectives. We show that model uncertainty is more important than estimation risk, and investors who discard model uncertainty face large utility losses.
Capital markets research in accounting
, 2001
"... I review empirical research on the relation between capital markets and financial statements.The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the politica ..."
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Cited by 78 (3 self)
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I review empirical research on the relation between capital markets and financial statements.The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the political process.The capital markets research topics of current interest to researchers include tests of market efficiency with respect to accounting information, fundamental analysis, and value relevance of financial reporting.Evidence from research on these topics is likely to be helpful in capital market investment decisions, accounting standard setting, and corporate financial
The Dog That Did Not Bark: A Defense of Return Predictability
, 2006
"... If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Longhorizon return forecasts give the same st ..."
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Cited by 73 (6 self)
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If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Longhorizon return forecasts give the same strong evidence. These tests exploit the negative correlation of return forecasts and dividendyield autocorrelation across samples, together with sensible upper bounds on dividendyield autocorrelation, to deliver more powerful statistics. I reconcile my findings with the literature that finds poor power in longhorizon return forecasts, and with the literature that notes the poor outofsample R² of returnforecasting regressions.
Learning about predictability: the effects of parameter uncertainty on dynamic asset allocation
, 2000
"... This paper examines the effects of uncertainty about the stock return predictability on optimal dynamic portfolio choice in a continuous time setting for a long horizon investor. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a s ..."
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Cited by 70 (3 self)
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This paper examines the effects of uncertainty about the stock return predictability on optimal dynamic portfolio choice in a continuous time setting for a long horizon investor. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a statedependent relation between the optimal portfolio choice and the investment horizon. There is substantial market timing in the optimal hedge demands, which is caused by stochastic covariance between stock return and dynamic learning. The opportunity cost of ignoring predictability or learning is found to be quite substantial.
Market liquidity as a sentiment indicator
, 2002
"... We build a model that helps explain why increases in liquidity⎯such as lower bidask spreads, a lower price impact of trade, or higher turnover⎯predict lower subsequent returns in both firmlevel and aggregate data. The model features a class of irrational investors, who underreact to the informatio ..."
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Cited by 63 (15 self)
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We build a model that helps explain why increases in liquidity⎯such as lower bidask spreads, a lower price impact of trade, or higher turnover⎯predict lower subsequent returns in both firmlevel and aggregate data. The model features a class of irrational investors, who underreact to the information contained in order flow, thereby boosting liquidity. In the presence of shortsales constraints, high liquidity is a symptom of the fact that the market is dominated by these irrational investors, and hence is overvalued. This theory can also explain how managers might successfully time the market for seasoned equity offerings, by simply following a rule of thumb that involves issuing when the SEO market is particularly liquid. Empirically, we find that: i) aggregate measures of equity issuance and share turnover are highly correlated; yet ii) in a multiple regression, both have incremental predictive power for future equalweighted market returns.