انحراف قیمت گذاری، ارزیابی غلط حرکت جمعی و شرایط اقتصاد کلان
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|13027||2013||15 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 13779 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Banking & Finance, Volume 37, Issue 12, December 2013, Pages 5285–5299
We measure an individual stock’s misvaluation based on the deviation of its price from predicted intrinsic value. Both under- and overvalued stocks identified by this misvaluation measure exhibit greater valuation uncertainty and arbitrage difficulty, and the misvaluation measure strongly predicts stock returns incremental to size, book-to-market ratio, past returns, and various return anomalies. Based on the misvaluation measure, we form a misvaluation factor and find that stock return covariances with this factor possess significant and robust return predictive power. We further show that the misvaluation factor predicts future economic conditions, providing additional insight into the real effect of systematic misvaluation in the stock market.
The existence of investors’ cognitive biases and arbitrage limits suggests that stock misvaluation cannot be fully eliminated by rational investors in the market, but rather is only corrected over time. Behavioral finance studies further predict that misvaluation comoves in the stock market. Such comovement could arise from fluctuations in market-wide sentiment, the common movements of noise traders, investors’ “style investment”, or retail investors’ common misperceptions of firms’ prospects and correlated trading (De Long et al., 1990, Barberis and Shleifer, 2003 and Kumar and Lee, 2006). These studies reveal that systematic retail sentiment or trading has incremental explanatory power for return comovement beyond the usual risk factors, which may result from the fact that retail investors move the market and contribute to the commonality in stock misvaluation. Motivated by the aforementioned studies, in this study, we examine misvaluation comovement and stocks’ systematic misvaluation in the market. We measure individual stocks’ misvaluation directly based on their pricing deviations from industry norms. Using the pricing deviation-based misvaluation measure, we form a misvaluation factor and examine whether loadings on this factor predict future stock returns. Furthermore, we explore the relation between the misvaluation factor and future states of the economy, which provides additional insight into the real effect of systematic misvaluation in the stock market. Our study is related to Hirshleifer and Jiang (2010). They identify common misvaluation across stocks based on firms’ debt and equity financing, and builds a financing-based misvaluation factor (UMO) from repurchase and new issue firms. 3 In contrast to their study, we measure misvaluation according to the difference between the observed market prices and predicted intrinsic values of individual stocks. We follow Rhodes-Kropf et al. (2005) in estimating a firm’s intrinsic value based on its book value, net income, and leverage, along with the pricing for each of these three components within the firm’s industry. Rhodes-Kropf et al. (2005) find that the three accounting variables explain around 80–94% of the within-industry variation in firm values, and define firm misvaluation as the deviation of the market price from the intrinsic value implied by the financial variables and contemporaneous industry pricing. 4 Many other studies also use this method to identify misvaluation in different contexts (e.g., Hertzel and Li, 2010 and Hoberg and Phillips, 2010), and we denote firm misvaluation as MSVF in this paper. The pricing deviation-based approach has several advantages over the financing-based approach of Hirshleifer and Jiang (2010) in the investigation of the relation between stock misvaluation and the cross section of expected stock returns. As it is not conditional on management’s behavior, it is not subject to the concern that firms may issue or retire shares for reasons other than mispricing.5 It measures misvaluation directly for individual stocks and thus allows us to examine the performance and characteristics of stocks with different degrees of misvaluation, which is difficult under the financing-based approach. Moreover, the pricing of UMO needs to be differentiated from the share issuance effect, as Pontiff and Woodgate (2008) argue that the latter drives the return predictability of firms’ financing activities. Our approach does not encounter such a challenge. Before testing the return predictability of MSVF, we first examine its association with various stock characteristics. We sort stocks into deciles based on MSVF and find that firm age, profitability, dividend-paying propensity, and asset tangibility all exhibit an inverted U-shaped pattern across the MSVF deciles, whereas the standard deviation of analysts’ forecasts and idiosyncratic volatility both display a U-shaped pattern. The evidence suggests that stocks with a higher degree of misvaluation, either under- or overvaluation, tend to be younger, less profitable, less likely to pay out dividends, and less tangible in addition to having lower greater dispersion in analysts’ forecasts and higher idiosyncratic volatility. According to Baker and Wurgler (2006), such stocks have greater valuation uncertainty and arbitrage difficulty, which could add to their degrees of misvaluation. 6 The evidence lends further support to the use of MSVF as a measure of stock misvaluation. Based on MSVF, we empirically test the relation between stock misvaluation and future returns. MSVF exhibits incremental return predictive power over conventional variables including size, book-to-market ratio, return reversal, and momentum. The control of the share issuance measure of Pontiff and Woodgate (2008), which captures firms’ financing activities in a broader way, has little influence on the relation between MSVF and returns, suggesting that MSVF captures misvaluation from a perspective that is different from that of firms’ financing activities. The results are also robust to the control of idiosyncratic volatility, operating accruals, asset growth, investment-to-asset ratio, leverage, and the changes in the market value of equity over the past five years. 7 To examine the commonality in misvaluation across stocks, we sort stocks based on MSVF and form a misvaluation factor (MSV) by measuring the returns on a factor-mimicking portfolio that goes long on stocks in the bottom 30% MSVF group (undervalued stocks) and short on stocks in the top 30% MSVF group (overvalued stocks) over the period from July 1968 to December 2011. MSV yields an average return of 0.78% per month, which remains significantly different from zero with a magnitude of 0.50% per month after controlling for market, size, book-to-market ratio, momentum, liquidity, investment, and leverage factors, along with the UMO factor of Hirshleifer and Jiang (2010). The Sharpe ratio associated with MSV is 0.35, which is higher than that of other factors. More importantly, we find that stock return covariances with the misvaluation factor, captured by stock loadings on MSV, are significantly positively related to future stock returns. The results hold at both the portfolio and individual stock levels, and the control of stock loadings on other return factors, including UMO, has little influence on the return predictive power of stocks’ sensitivities to MSV. In addition, we find that the return predictive powers of stock loading on the misvaluation factor and the firm misvaluation measure MSVF are not subsumed by each other. As the loading on MSV captures comovement with market-wide misvaluation and the characteristic measure MSVF captures both systematic and idiosyncratic misvaluation, the evidence is in line with the conjecture of Daniel et al. (2005) that both misvaluation components can act as return predictors. Finally, to further our understanding of the relation between systematic misvaluation and the cross section of expected stock returns, we examine the relation between the misvaluation factor and future economic conditions. We conjecture that MSV contains information on market-wide misvaluation and therefore could help to predict future states of the economy. The empirical results show that MSV is positively related to the correction of average misvaluation across individual stocks. A high MSV indicates faster correction of misvaluation, which is likely to be followed by improving resource allocation efficiency in the real economy. A low MSV, on the contrary, suggests that misvaluation is prevailing in the stock market, which could be value-destroying through distorting the decision-making of market participants. We thus expect a higher (lower) MSV to be associated with a lower (higher) probability of future recession. The empirical results support our prediction. MSV is significantly negatively related to the likelihood of future recession, and the result is robust to the control of other conventional return factors. The evidence further implies that stocks that comove more with the undervalued stocks are better able to prosper than stocks that comove more with the overvalued stocks when good states of the economy are expected, which sheds light on the return forecasting power of individual stocks’ sensitivities to the misvaluation factor. Our findings challenge the classical view of asset pricing, and contribute to the literature by providing additional evidence of stock return comovement arising from market inefficiency.8 This paper also supplements Hirshleifer and Jiang (2010) by providing further evidence of misvaluation comovement using a distinct approach in identifying stock misvaluation. By exploring the information content of commonality in misvaluation and examining the relation between the misvaluation factor and future states of the economy, this paper enriches our understanding of the real effect of systematic misvaluation in the stock market. The rest of this paper is organized as follows. Section 2 describes our data and methodology, Section 3 examines the stock properties associated with the pricing deviation-based misvaluation measure, Section 4 investigates the relation between stock misvaluation and future stock returns, Section 5 describes the formation of the misvaluation factor and tests the return predictive power of loadings on the factor, and Section 6 examines the relation between the misvaluation factor and future states of the economy. Section 7 concludes the paper.
نتیجه گیری انگلیسی
In this paper, we measure the misvaluation of individual stocks directly based on the deviation of their market prices from predicted intrinsic values. We find that stocks with greater degrees of misvaluation, either under- or overvaluation, tend to have higher valuation uncertainty and arbitrage difficulty. The misvaluation measure has strong return predictive power beyond that of size, book-to-market, return reversal, momentum, accrual, asset growth, the share issuance effect, the investment effect, the leverage effect, and the five-year changes in the market value of equity. Based on the stock misvaluation measure, we build a misvaluation factor by longing undervalued stocks and short-selling overvalued stocks. The variation in the misvaluation factor could not be fully explained by conventional return factors and the financing-based misvaluation factor of Hirshleifer and Jiang (2010). It earns around 50% excess monthly returns after the control of the Fama–French three factors, momentum, liquidity, investment, leverage, and the financing-based misvaluation factor, and achieves a Sharpe ratio of 0.35, which is higher than that of other factors. More importantly, we show that stocks’ return covariances with the misvaluation factor are significantly positively related to future returns at both the portfolio and individual stock levels. The results confirm that misvaluation comoves in the market and that systematic misvaluation possesses return predictive power. In addition, we find that the return predictive power of stock loadings on the misvaluation factor and the firm misvaluation measure are not subsumed by each other, suggesting that both systematic and idiosyncratic misvaluation contain information about expected stock returns. Finally, we examine the relation between the misvaluation factor and future economic conditions. Returns on the misvaluation factor portfolio MSV are more volatile during contraction than during expansion, and strongly predict the likelihood of future recession. The predictability may stem from the association between MSV and the correction of mispricing in the stock market. A high MSV indicates faster correction of misvaluation at the aggregate level, thus is likely to be followed by improving resource allocation efficiency and better future economic conditions. A low MSV, on the contrary, implies slow correction or even aggravation of market-wide misvaluation, which is likely to be followed by resource misallocation and worsening states of the economy. The relation between MSV and future economic conditions furthers our understanding of the influence of systematic equity misvaluation on the real economy. It also suggests that the return predictive power of stock loadings on the misvaluation factor could result not only because the misvaluation factor captures the commonality in misvaluation across stocks, but also because it signals changes in future economic prospects, which in turn affect the returns of stocks with different sensitivities to the misvaluation factor. This study is not without limitations. The misvaluation measure used in this paper is adopted from Rhodes-Kropf et al. (2005), and relies on the industry-adjusted pricing of several fundamental variables in measuring the true value of individual stocks and their degrees of misvaluation. However, there is possibility that the industry-level adjustment is not sufficient and there is risk not captured by the fundamental variables considered in the pricing model. Thus the misvaluation measure could still proxy for stocks’ exposures to risk and a risk-based alternative cannot be completely ruled out. Nevertheless, the evidence that the misvaluation measure is associated with stocks’ valuation uncertainty and arbitrage difficulty, as well as the fact that the control of stocks’ sensitivities to conventional risk factors has little influence on the return predictive power of the misvaluation measure, are both supportive of the argument that the measure captures, at least to some degree, the mispricing of stocks.