The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

The implied liquidity premium for equities

Over the long term, the returns on smaller stocks are likely to be higher than the returns on larger stocks. This phenomenon has been called size effect, and a number of explanations have been proposed to account for it. Here we show that the difference in return between the larger and the smaller stocks can be accounted for by a liquidity premium for the smaller stocks, and we estimate the value of this premium using structural parameters for the capital distribution of the U.S. stock market during the 1990s The authors wish to express their gratitude to an anonymous referee for a very thorough and incisive reading, as well as for many constructive suggestions that have significantly improved this paper. The authors wish to express their gratitude to an anonymous referee for a very thorough and incisive reading, as well as for many constructive suggestions that have significantly improved this paper.     

How many factors are important in U.K. stock returns?

I use the sequential approach of Harvey and Liu ([2018]. Lucky factors (Working Paper). Duke University) to build linear factor models in U.K. stock returns among a set of 13 candidate factors using individual stocks and three groups of test portfolios between July 1983 and December 2017. My study finds that the Market factor is the dominant factor in reducing mispricing in individual stocks and test portfolios regardless of the pricing error metric used. The Market factor has a bigger impact when using a value weighting pricing error metric. Whether a second factor is used or not depends upon which metric is used for mispricing and the time period examined. My study finds support for a two-factor model for the whole sample period of the Market factor and the Conservative Minus Aggressive (CMA) factor of Fama and French ([2015]. “A five-factor asset pricing model.” Journal of Financial Economics 116: 1–22) when giving greater weight to the mispricing of larger companies.     

Conditional Equity Premium and Aggregate Corporate Investment

We document a strong negative relation between aggregate corporate investment and conditional equity premium estimated from direct stock market risk measures. Consistent with the investment-based asset pricing model, the comovement with conditional equity premium fully accounts for aggregate investment's market return predictive power. Similarly, conditional equity premium is a significant determinant of classic Tobin's q measure, although q has much weaker explanatory power for aggregate investment possibly because of its measurement errors. Moreover, the positive relation between aggregate investment and investor sentiment documented in previous studies reflects the fact that both variables correlate closely with conditional equity premium.     

Market Expectations in the Cross‐Section of Present Values

Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross‐section of book‐to‐market ratios, we find an out‐of‐sample return forecasting R² of 13% at the annual frequency (0.9% monthly). We document similar out‐of‐sample predictability for returns on value, size, momentum, and industry portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratios in a latent factor system. Spreads in value portfolios’ exposures to economic shocks are key to identifying predictability and are consistent with duration‐based theories of the value premium.     

An Empirical Investigation of Eastern European Bond Markets

We examine the value of Eastern European emerging bond markets to global fixed income managers. In an environment where bonds from traditional developed markets are offering modest yields, emerging market bonds with attractive yields are becoming more popular with institutional managers. Furthermore, the returns on these bonds exhibit low correlations with traditional fixed income investments and thus offer opportunities for portfolio diversification. We develop a multifactor forecasting model and estimate its parameters using a dynamic Kalman filter procedure. The forecasts are then used to construct optimal mean–variance portfolios with and without emerging market bonds. We find that the portfolios that include emerging market bonds have significantly higher Sharpe ratios.     

Decomposing the VIX: Implications for the predictability of stock returns

The VIX index is not only a volatility index but also a polynomial combination of all possible higher moments in market return distribution under the risk-neutral measure. This paper formulates the VIX as a linear decomposition of four fundamentally different elements: the realized variance (RV), the variance risk premium (VRP), the realized tail (RT), and the tail risk premium (TRP), respectively. Using an innovative and nonparametric tail risk measure, we find that approximately one-third of the VIX's formation is attributed to the TRP. In addition to VRP, RT and TRP are crucial components for predicting future returns on equity portfolios.     

Volatility Risk Premium,Risk Aversion,and the Cross‐Section of Stock Returns

We test if innovations in investor risk aversion are a priced factor in the stock market. Using 25 portfolios sorted on book‐to‐market and size as test assets, our new factor together with the market factor explains 64% of the variation in average returns compared to 60% for the Fama‐French model. The new factor is generally significant with an estimated risk premium close to its time series mean also when industry portfolios and portfolios sorted on previous returns are augmented to the test assets.     

Components of Market Risk and Return

This article proposes a flexible but parsimonious specificationof the joint dynamics of market risk and return to produce forecastsof a time-varying market equity premium. Our parsimonious volatilitymodel allows components to decay at different rates, generatesmean-reverting forecasts, and allows variance targeting. Thesefeatures contribute to realistic equity premium forecasts forthe U.S. market over the 1840–2006 period. For example,the premium forecast was low in the mid-1990s but has recentlyincreased. Although the market's total conditional variancehas a positive effect on returns, the smooth long-run componentof volatility is more important for capturing the dynamics ofthe premium. This result is robust to univariate specificationsthat condition on either levels or logs of past realized volatility(RV), as well as to a new bivariate model of returns and RV.     

The Piotroski F‐score: evidence from Australia

A market‐neutral strategy that is long [short] stocks with a high [low] Piotroski F‐score generates an index‐weighted 0.8 percent pm on S&P/ASX 200 stocks and 1.4 percent pm on smaller stocks. Equal‐weighted returns are higher and in all cases returns are statistically significant. However, the Carhart model alphas are not statistically significant except in the case of equal‐weighted small cap portfolios. For such portfolios, however, most of the alpha comes from the short side and most institutional investors would find them uninvestable due to capacity constraints. A range of tests indicate that analyst neglect does not explain the F‐score premium.     

Risk,Mispricing, and Value Investing

We evaluate the stock return performance of a modified version of the book-to-market strategy and its implications for market efficiency. If the previously documented superior stock return of the book-to-market strategy represents mispricing, its performance should be improved by excluding fairly valued firms with extreme book-to-market ratios. To attain this, we classify stocks as value or glamour on book-to-market ratios and accounting accruals jointly. This joint classification is likely to exclude stocks with extreme book-to-market ratios due to mismeasured accounting book values reflecting limitations underlying the accounting system. Using both 12-month buy-and-hold returns and earnings announcement returns, our results show that this joint classification generates substantially higher portfolio returns in the post-portfolio-formation year than the book-to-market classification alone with no evidence of increased risk. In addition, this superior stock return performance is more pronounced among firms held primarily by small (unsophisticated) investors and followed less closely by market participants (stock price <$10). Finally, and most importantly, financial analysts are overly optimistic (pessimistic) about earnings of glamour (value) stock, and for a subset of firms identified as overvalued by our strategy, the earnings announcement raw return, as well as abnormal return, is negative. These last results are particularly important because it is hard to envision a model consistent with rational investors holding risky stocks with predictable negative raw returns for a long period of time rather than holding fT-bills and with financial analysts systematically overestimating the earnings of these stocks while underestimating earnings of stocks that outperform the stock market.     

Interaction of size,book‐to‐market and momentum effects in Australia

This study seeks to disentangle the effects of size, book‐to‐market and momentum on returns. Initial results show that each characteristic has a role in explaining returns, but that there is interaction between size and momentum, as well as between size and book‐to‐market. Three key findings emerge. First, the size premium is the strongest, particularly in the loser portfolios. Second, the value premium is generally limited to the smallest portfolios. Third, the momentum premium is evident for the large‐ and middle‐sized portfolios, but loser stocks significantly outperform winner stocks in the smallest size portfolio. When these interactions are controlled with multivariate regression, we find a significant negative average relation between size and returns, a significant positive average relation between book‐to‐market and returns, and a significant positive average relation between momentum and returns.     

New Paradigms in Stock Market Indexing

Considerable recent interest has been shown in a new set of stock‐market indices that are weighted by fundamental factors such as sales, earnings, dividends or book values, rather than by capitalization. In this paper, we analyze the performance of Fundamental Indexing? (“FI”). First, we show that the source of FI's recent excellent performance is not from its ability to systematically arbitrage mispricing in a noisy market but from increasing the portfolio's exposure to stocks with low price‐to‐book values and with small capitalizations. We find that FI does not produce a positive alpha when its excess returns are explained by the Fama‐French three‐factor model of CAPM beta, the value premium and the size premium. Second, we show that it is possible to construct a portfolio of exchange‐traded funds with similar factor loadings that can replicate, and sometimes, even outperform FI. However, we caution investors not to expect consistent outperformance from portfolios tilted towards value and small‐cap stocks. Historical data shows evidence of mean reversion in the performance of such strategies.     

The Return to Direct Investment in Private Firms: New Evidence on the Private Equity Premium Puzzle*

This paper uses a novel dataset to analyze the return to direct investments in private firms by pension funds. We have two key findings. First, direct investments in private firms have underperformed public equity by 392 basis points per annum under conservative risk adjustments. Second, initial mispricing, due to over‐optimism or misperceived risk, and subsequent low capital gains seem to explain the gap in returns to private firms. Overall, these findings complement the finding of Moskowitz and Vissing‐Jørgensen (2002) of low returns on entrepreneurial investments and provide new insight into the existence of what they call the private equity premium puzzle: Even professional investors with well‐diversified portfolios like pension funds seem to get a poor risk‐return tradeoff from investing directly in private firms.     

The Performance of Characteristics‐based Indices1

This paper analyses a set of characteristics‐based indices that, it has been argued, outperform market cap‐weighted indices. We analyse the performance of an exhaustive list of these indices and show that i) the outperformance over value‐weighted indices may be negative over long time periods, and ii) there is no significant outperformance over equal‐weighted indices. An analysis of the style and sector exposures of characteristics‐based indices reveals a significant value tilt. When this tilt is properly adjusted for, the abnormal returns of these indices decrease considerably. Moreover, it is straightforward to construct portfolios with higher Sharpe ratios than characteristics‐based indices through factor or sector tilts.     

Volatility transmission in the UK equity market

In this study, the three-factor model of Fama and French and the ‘characteristic model’ of Daniel and Titman are tested using the French Stock Market. Stocks are ranked by size and book to market ratio and then by ex-ante β, HML or SMB loadings. Based on average returns, results reject the factor model with ‘characteristic balanced’ portfolios. In contrast, in time-series regressions, results are consistent with the factor pricing model and inconsistent with the characteristic-based pricing model. Because the value premium is small, conclusions must be interpreted carefully. However, size and market premiums allow more powerful tests of the two models.     

Accrual mispricing,value-at-risk,and expected stock returns

We investigate the extent to which a parsimonious measure of maximum likely loss that captures the tail risk of returns—known as value-at-risk (VaR)—explains the relationship between accruals and the cross-sectional dispersion of expected stock returns. We construct portfolios based on Sloan’s (Account Rev 71(3):289–315, 1996) total accruals (TA) measure and individual asset-level VaR, which reflects the dynamic behavior of the asset distribution. We document that VaR is in congruence with portfolio-level accruals and that there is a significant positive relationship between VaR and the cross-section of portfolio returns. Allowing a double-sort involving VaR and TA further suggests that the spread between low- and high-TA portfolios is significantly attenuated after controlling for VaR. We also conduct a firm-level cross-sectional regression analysis and demonstrate that the TA- and VaR-based characteristics—but not the factor-mimicking portfolios—are compensated with higher expected returns, and that VaR neither subsumes nor is subsumed by TA. Finally, our cross-sectional decomposition analysis suggests that the firm-level VaR captures at least 7% of the accrual premium even in the presence of size and book-to-market. These findings lend support for the mispricing explanation of the accrual anomaly.

     

m-Double Poisson Lévy markets

We develop novel mispricing of markets under asymmetric information and jumps for informed and uninformed investors, called m-Double Poisson markets, driven by independent Double Poisson processes. In the special case m?=?1, called the Double Poisson pure-jump Lévy market, both types of investors hold the same optimal portfolio and expected utility, and hence, the informed investor has no utility advantage over the uninformed. For the general market, instantaneous centralized moments of returns are used to compute optimal portfolios and utilities. The mean, variance, skewness and kurtosis of instantaneous returns are reported using jump amplitudes and frequencies.     

Can mispricing explain the value premium?

Empirical research finds that stocks with low market-to-book (MTB) ratios outperform stocks with high MTB ratios. Rhodes-Kropf, Robinson, and Viswanathan separate the MTB ratio into mispricing and growth options components. We report that the mispricing component, but not the growth options component, predicts abnormal returns for up to 5 years. We also find that the mispricing component, but not the growth options component, provides incremental information relative to existing asset pricing models. Moreover, after controlling for mispricing, value no longer beats growth. Overall, our evidence is consistent with a behavioral explanation of the value premium.     

Empirical Evidence of the Existence of Investable Premiums in Emerging Market Investable Stocks

This paper shows that portfolios of more investable securities bear a premium when compared to portfolios of less investable stocks, reflecting compensation for local risk factors. The investable premium is overwhelmingly priced across 3,782 companies traded in 29 emerging markets from 1988 to 2006. The investable premium impacts stock returns at least as much as other fundamental premiums such as size, value, momentum, and loads on political, economic, and financial risk factors. The impact of the investable premium on emerging stocks returns has increased in strength, implying that foreign ownership has greater influence on local markets in recent years.