Detecting time-variation in corporate bond index returns: A smooth transition regression model

This paper investigates the time-varying corporate bond index returns in a multi-factor smooth transition regression model. We find that expected index returns vary between weak and strong economic regimes, where the transition from one regime to the other is governed by the 3-quartered growth of industrial production. Weak economic regimes are characterized by low growth of industrial production, vice versa for strong economic regimes. Further, risk factor sensitivities are generally more negative in strong economic regimes than in weak regimes, implying that index returns are low when economic conditions are good and high when economic conditions are poor.     

Returns to scale and asset prices

The q‐theory of investment is proposed to explain firm growth effects, where previous papers identify a negative effect of firm growth, including asset growth, real investment and net share issuance, on future stock returns. This paper uses returns to scale from the production function to test the dynamic q‐theory, which predicts that the firm growth effect is theoretically weaker for firms with decreasing returns to scale (DRS) than for non‐DRS firms. Our empirical results generally support the prediction of dynamic q‐theory. However, we find that the dynamic q‐theory explains little of the value, momentum and ROE effects from the standpoint of returns to scale.     

Information technology,contextual factors and the volatility of firm performance

This study uses previous theory developed in the IT implementation literature and the information processing view of the firm to empirically investigate the impact of IT investments and several contextual variables on the volatility of future earnings. We use InformationWeek 500 data on IT spending from 1992–1997 to find evidence that IT investments increase the volatility of future earnings but that this impact is highly contingent upon three firm level contextual factors — sales growth, unrelated diversification, and size. These factors can lead to conditions in which IT increases or reduces earnings volatility. Taken together, these results may help explain what has recently been termed the “new productivity paradox,” i.e., the apparent under-investment in information technology despite evidence of highly positive returns for doing so, and suggests settings where managers may be under- or over-discounting returns on IT investments.     

Time-varying expected momentum profits

This paper examines the time variations of expected momentum profits using a two-state Markov switching model with time-varying transition probabilities to evaluate the empirical relevance of recent rational theories of momentum profits. We find that in the expansion state the expected returns of winner stocks are more affected by aggregate economic conditions than those of loser stocks, while in the recession state the expected returns of loser stocks are more affected than those of winner stocks. Consequently, expected momentum profits display strong procyclical variations. We argue that the observed momentum profits are the realization of such expected returns and can be interpreted as the procyclicality premium. We provide a plausible explanation for time-varying momentum profits through the differential effect of leverage and growth options across business cycles.     

Real investment and risk dynamics

We ask to what extent the negative relation between investment and average stock returns is driven by risk. We show that: (i) the average return spread between low and high asset growth and investment portfolios is largely accounted for by their spread in systematic risk, as measured by the loadings on the Chen, Roll, and Ross (1986) factors; (ii) as predicted by q-theory and real options models, systematic risk falls during large investment periods; (iii) the returns of factors formed on the investment-to-assets, asset growth, and investment growth all forecast aggregate economic activities. Our evidence suggests that risk plays an important role in explaining the investment-return relation.     

Connecting Optimal Capital Investment and Equity Returns

Economic theory predicts a contemporaneous correlation between equity returns and investment growth that is only weakly present in the data. By modifying the firm's production function to include a lag between investment decisions and expenditures, and after correcting for the temporal aggregation of investment, I find the predicted correlation to be present in the data. I estimate the model for 31 industries and find that investment returns are highly correlated with the industry portfolio equity returns. Further, the portion of investment returns orthogonal to equity returns is associated positively with changes in profitability and negatively with lagged differences between equity and investment returns.     

Investor attention,ETF returns,and country-specific factors

Using the data of 47 single-country exchange-traded funds (ETFs) traded in the U.S. from 36 countries during 2004–2017, this research examines the impact of investor attention proxied by Google Search Volume Index and home country-specific factors on different quantile of their returns. Evidence first shows that compared with U.S. investor attention, home country investor attention largely correlates with low to medium ETF returns, supporting the attention-induced price pressure hypothesis. Second, home country-specific factors significantly affect ETF returns at different conditional quantiles. We also find that investors prefer investing in a country with strong similarity to that of the U.S., supporting the cross-country information asymmetry hypothesis. Third, an intervening effect of home country-specific factors exists on the relationship between U.S. investor attention and ETF returns. These findings should help government authorities find appropriate strategies to attract foreign investment and upgrade the value of their capital market as well as provide a reference on efficiency for equity investors.     

Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment

Evidence suggests that expected excess stock market returns vary over time, and that this variation is much larger than that of expected real interest rates. It follows that a large fraction of the movement in the cost of capital in standard investment models must be attributable to movements in equity risk-premia. In this paper we emphasize that such movements in equity risk premia should have implications not merely for investment today, but also for future investment over long horizons. In this case, predictive variables for excess stock returns over long-horizons are also likely to forecast long-horizon fluctuations in the growth of marginal Q, and therefore investment. We test this implication directly by performing long-horizon forecasting regressions of aggregate investment growth using a variety of predictive variables shown elsewhere to have forecasting power for excess stock market returns.     

Explaining the accrual anomaly by market expectations of future returns and earnings

This study examines the accrual anomaly under the framework of the Campbell [Campbell, J.Y. (1991). A variance decomposition for stock returns. Economic Journal 101 (405), 157-179.] model. The Campbell (1991) model shows that realized asset returns are a joint function of 1) expected returns, 2) revisions in market expected future returns (i.e., return news), and 3) revisions in market expected future cash flows (i.e., cash flow news). The current study adopts the Easton [Easton, P. (2004). PE ratios, PEG ratios, and estimating the implied expected rate of return on equity capital. The Accounting Review 79 (1), 73-96.] model to estimate proxies for expected returns, return news, and cash flow news. The results show that firms with low accruals have lower expected returns than firms with high accruals, which is contradictory to prior research that argues that firms with low accruals are more risky. However, investors underestimate (overestimate) future earnings growth, a proxy for cash flow growth, for low (high) accrual firms. Further analysis demonstrates that earnings news (proxy for cash flow news) plays a major role in explaining abnormal returns associated with the accrual anomaly.     

Limits-to-arbitrage, investment frictions, and the asset growth anomaly

We empirically evaluate the predictions of the mispricing hypothesis with limits-to-arbitrage suggested by Shleifer and Vishny (1997) and the q-theory with investment frictions proposed by Li and Zhang (2010) on the negative relation between asset growth and average stock returns. We conduct cross-sectional regressions of returns on asset growth on subsamples split by a given measure of limits-to-arbitrage or investment frictions. We show that: (i) proxies for limits-to-arbitrage and proxies for investment frictions are often highly correlated; (ii) the evidence based on equal-weighted returns shows significant support for both hypotheses, while the evidence from value-weighted returns is weaker; and (iii) in direct comparisons, each hypothesis is supported by a fair and similar amount of evidence.     

The value premium,aggregate risk innovations,and average stock returns

We test whether innovations in aggregate risk, interpolated from a vector autoregressive system that contains the Chen et al. (1986) five factors as in Petkova (2006), are common factors in cross-sectional stock returns. We provide direct evidence that innovation in industrial production growth, a classical business-cycle variable that summarizes the state of the economy, is associated with the cross-sectional return predictability of individual stocks. We conclude that the role of innovation in aggregate risk is not random, and furthermore that it provides guidance concerning an important source of nonfinancial market-based risk in asset returns.     

Does q-theory with investment frictions explain anomalies in the cross section of returns?

Q-theory predicts that investment frictions steepen the relation between expected returns and firm investment. Using financing constraints to proxy for investment frictions, we show only weak evidence that the investment-to-assets and asset growth effects in the cross section of returns are stronger in financially more constrained firms than in financially less constrained firms. There is no evidence that q-theory with investment frictions explains the investment growth, net stock issues, abnormal corporate investment, or net operating assets anomalies. Limits-to-arbitrage proxies dominate q-theory with investment frictions in explaining the magnitude of the investment-to-assets and asset growth anomalies in direct comparisons.     

How do accounting variables explain stock price movements? Theory and evidence

This paper provides theory and evidence showing how accounting variables explain cross-sectional stock returns. Based on Zhang, G. [2000. Accounting information, capital investment decisions, and equity valuation: theory and empirical implications. Journal of Accounting Research 38, 271–295], who relates equity value to accounting measures of underlying operations, we derive returns as a function of earnings yield, equity capital investment, and changes in profitability, growth opportunities, and discount rates. Empirical results confirm the predicted roles of all identified factors. The model explains about 20% of the cross-sectional return variation, with cash-flow-related factors (as opposed to changes in discount rates) accounting for most of the explanatory power. The properties of the model are robust across various subsamples and periods.     

Systematic risk and the cross section of hedge fund returns

This paper investigates the extent to which market risk, residual risk, and tail risk explain the cross-sectional dispersion in hedge fund returns. The paper introduces a comprehensive measure of systematic risk (SR) for individual hedge funds by breaking up total risk into systematic and fund-specific or residual risk components. Contrary to the popular understanding that hedge funds are market neutral, we find that systematic risk is a highly significant factor explaining the dispersion of cross-sectional returns while at the same time measures of residual risk and tail risk seem to have little explanatory power. Funds in the highest SR quintile generate 6% more average annual returns compared with funds in the lowest SR quintile. After controlling for a large set of fund characteristics and risk factors, systematic risk remains positive and highly significant, whereas the relation between residual risk and future fund returns continues to be insignificant. Hence, systematic risk is a powerful determinant of the cross-sectional differences in hedge fund returns.     

Normative portfolio theory

In this paper, we correct the adverse impact of estimation risk on both portfolio weights and performance with two new equity allocation methods we implement with estimation-free and estimated ex-ante returns. Portfolios with estimation-free ex-ante returns and systematic-to-unsystematic risk weights have statistically higher Sharpe ratios than both similar portfolios with estimated ex-ante returns and 1/N′th portfolios. Optimal portfolio methods with well-behaved weights guide investors in a way not hitherto possible (normative portfolio theory).     

Liquidity costs,idiosyncratic volatility and expected stock returns

This paper considers liquidity as an explanation for the positive association between expected idiosyncratic volatility (IV) and expected stock returns. Liquidity costs may affect the stock returns, through bid-ask bounce and other microstructure-induced noise, which will affect the estimation of IV. We use a novel method (developed by Weaver, 1991) to eliminate microstructure influences from stock closing price-based returns and then estimate IV. We show that there is a premium for IV in value-weighted portfolios, but this premium is less strong after correcting returns for microstructure bias. We further show that this premium is driven by liquidity in the prior month after correcting returns for microstructure noise. The pricing results from equally-weighted portfolios indicate that IV does not predict returns either before or after controlling for liquidity costs. These findings are robust after controlling for common risk factors as well as analysing double-sorted portfolios based on IV and liquidity.     

International tests of a five-factor asset pricing model

Average stock returns for North America, Europe, and Asia Pacific increase with the book-to-market ratio (B/M) and profitability and are negatively related to investment. For Japan, the relation between average returns and B/M is strong, but average returns show little relation to profitability or investment. A five-factor model that adds profitability and investment factors to the three-factor model of Fama and French (1993) largely absorbs the patterns in average returns. As in Fama and French, 2015, Fama and French, 2016, the model's prime problem is failure to capture fully the low average returns of small stocks whose returns behave like those of low profitability firms that invest aggressively.     

Profitability,investment and average returns

Valuation theory says that expected stock returns are related to three variables: the book-to-market equity ratio (B_t/M_t), expected profitability, and expected investment. Given B_t/M_t and expected profitability, higher expected rates of investment imply lower expected returns. But controlling for the other two variables, more profitable firms have higher expected returns, as do firms with higher B_t/M_t. These predictions are confirmed in our tests.     

Expected returns and expected dividend growth

We investigate a consumption-based present-value relation that is a function of future dividend growth and find that changing forecasts of dividend growth are an important feature of the post-war U.S. stock market, despite the failure of the dividend–price ratio to uncover such variation. In addition, dividend forecasts are found to covary with changing forecasts of excess stock returns over business cycle frequencies. This covariation is important because positively correlated fluctuations in expected dividend growth and expected returns have offsetting effects on the log dividend–price ratio. The market risk premium and expected dividend growth thus vary considerably more than is apparent using the log divided–price ratio alone as a predictive variable.