Oil Risk Exposure: The Case of the U.S. Oil and Gas Sector

We estimate oil price risk exposures of the U.S. oil and gas sector using the Fama‐French‐Carhart's four‐factor asset pricing model augmented with oil price and interest rate factors. Results show that the market, book‐to‐market, and size factors, as well as momentum characteristics of stocks and changes in oil prices are significant determinants of returns for the sector. Oil price risk exposures of U.S. oil and gas companies in the oil and gas sector are generally positive and significant. Our study also finds that oil price risk exposures vary considerably over time, and across firms and industry subsectors.     

Asset Pricing with a Bank Risk Factor

This paper studies how the state of the banking sector influences stock returns of nonfinancial firms. We consider a two‐factor pricing model, where the first factor is the traditional market excess return and the second factor is the change in the average distance to default of commercial banks. We find that this bank factor is priced in the cross section of U.S. nonfinancial firms. Controlling for market beta, the expected excess return for a stock in the top quintile of bank risk exposure is on average 2.83% higher than for a stock in the bottom quintile.     

Asset liquidity and stock returns

We document the significant predictive power of firms' asset liquidity in the cross section of subsequent stock returns. The annual return spread between portfolios featuring the highest and lowest levels of asset liquidity is significantly positive. Our proposed measure of asset liquidity outperforms those measures developed by Gopalan et al. (2012) in predicting returns. The asset liquidity anomaly also provides significantly positive alphas when controlling for the asset pricing factors in the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model. Asset liquidity exhibits strong return forecasting power even after controlling for acknowledged cross-sectional determinants of return. The positive relation between asset liquidity and future returns tends to be stronger for firms with greater asset productivity, higher quality cash flow and lower capital investment.     

Asset pricing with a reference level of consumption: New evidence from the cross-section of stock returns

This paper presents an empirical evaluation of recently proposed asset pricing models which extend the standard preference specification by a reference level of consumption. We motivate an alternative model that accounts for the return on human capital as a determinant of the reference level. Our analysis is based on a broad cross-section of test assets, which provides a level playing field for a comparison to established benchmark models. The reference level model extended by human capital does a good job in explaining size and value premia. Estimated on Fama and French's size and book-to-market sorted portfolios, it outperforms Lettau and Ludvigson's scaled CCAPM and delivers average pricing errors comparable to the Fama-French three-factor model.     

Financial constraints and stock returns — Evidence from Australia

Using multiple discriminant analysis, we construct an index that measures firms' external financial constraints in an Australian setting. We form portfolios of firms based on our financial constraints index and find that financially constrained firms earn lower return than their unconstrained counterparts. Moreover, stock returns of financially constrained firms are found to move together, indicating the potential existence of a financial constraints factor. Neither the variation nor the mean return of the constraints factor are well explained by existing asset pricing models, suggesting an independent role for our financial constraints factor in affecting stock returns.     

Asset pricing and energy consumption risk

This paper proposes energy consumption in the US as a new measure for the consumption capital asset pricing model. We find that (i) industrial energy growth produces reasonable values for the relative risk aversion coefficient and the implied risk-free rate; (ii) compared to alternative consumption measures, industrial energy performs well in explaining the cross-sectional variation in stock returns with the lowest implied risk aversion and pricing errors; (iii) the industrial energy consumption risk model performs equally well as the Fama–French three-factor model in the cross-sectional asset pricing tests; and (iv) total energy consumption risk is priced in the presence of the Fama–French factor risks.     

Book Assets,Real Estate,and Returns on Common Stock

Since real estate is common to most firms, this study examines whether there is a real estate factor in common stock returns that is not completely captured by existing asset pricing models. The three-factor model of Fama and French (1993), hereafter FF, is extended to incorporate a unique real estate factor. Using his extended-FF model, we examine the returns on 53 industry portfolios of common stocks over the 1972 through 1995 time period. The results indicate that a significant 19 percent of the industries are systematically related to the real estate factor. Most interestingly, we show that the loading of the real estate factor in common stock return is related to the loading of the book-to-market equity factor in these returns. We also construct decile portfolios of common stocks based on historical sensitivities of common stock returns to the real estate factor. The coefficients on the real estate factor vary systematically across the decile portfolios. The results of our analysis suggest that portfolio managers should manage their exposure to real estate.     

Does the Pricing of Financial Reporting Quality Change Around Dividend Changes?

We examine whether accrual earnings quality is a priced information risk factor in a dividend change setting. We define information risk as the probability that firm‐specific financial statement information pertinent to investor pricing decisions is of low precision, and use the factor‐mimicking portfolio returns formed on the Dechow‐Dichev [2002] accrual quality (AQ) metric to proxy for the information risk (IR) factor returns. We augment the Fama‐French three‐factor model with this IR factor, and find that dividend initiation and increase firms exhibit a decrease in the factor loadings on the IR factor while dividend decrease firms exhibit an increase in the corresponding factor loadings, but such changes in the factor loadings occur months prior to the dividend change announcements. The results are robust to further controls for operating risk and using an alternative measure of information risk. Further analysis on changes in information characteristics such as AQ, the probability of informed trading score (PIN), forecast dispersion, and return volatility surrounding dividend change events are consistent with the asset pricing results. Overall, we interpret our results as being consistent with investors treating the information risk associated with the precision of financial statement information as a priced risk factor, with both the precision and pricing changing in predictable directions around dividend changes. However, while we attempt to control for operating risk changes in additional tests, we cannot completely rule out changes in operating risk as a competing alternative explanation for our observed results.     

In America's thrall: the effects of the US market and US security characteristics on Australian stock returns

Can Australian equity returns be modelled by ‘home‐grown’ factors? We examine the indigenous capital asset pricing model, the indigenous Fama–French three‐factor model, and extensions to the latter, and find them all wanting. We find evidence of domestic market segmentation in Australia. For the smallest firms, all the models we study fail. For the largest Australian firms, we find that the US Fama–French three factors (downloaded from French's website: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ ) provide a successful model of Australian returns. It is as if the largest firms in the Australian market are simply part of the larger US market.     

Earnings Quality, Insider Trading, and Cost of Capital

Previous research argues that earnings quality, measured as the unsigned abnormal accruals, proxies for information asymmetries that affect cost of capital. We examine this argument directly in two stages. In the first stage, we estimate firms' exposure to an earnings quality factor in the context of a Fama‐French three‐factor model augmented by the return on a factor‐mimicking portfolio that is long in low earnings quality firms and short in high earnings quality firms. In the second stage, we examine whether the earnings quality factor is priced and whether insider trading is more profitable for firms with higher exposure to that factor. Generally speaking, we find evidence consistent with pricing of the earnings quality factor and insiders trading more profitably in firms with higher exposure to that factor.     

An Empirical Comparison of Asset-Pricing Models in the Shanghai A-Share Exchange Market

This paper evaluates and compares the performance of three-asset pricing models—the capital asset pricing model of Sharpe (J Finance 19:425–442, 1964), the three-factor model of Fama and French (J Financ Econ 33:3–56, 1993), and the five-factor model (Fama and French in J Financ Econ 123:1–22, 2015)—in the Shanghai A-share exchange market. Our results do not support the superiority of the five-factor model and show that the three-factor model outperforms the other models. We also verify the redundancy of the book-to-market factor and confirm the findings of Fama and French (2015).     

Asset Pricing and the Illiquidity Premium

In this paper, we examine the asset‐pricing role of liquidity (as proxied by share turnover) in the context of the Fama and French (1993) three‐factor model. Our analysis employs monthly Australian data, covering the sample period from 1990 to 1998. The key finding of our research is that the main test is unable to reject the test of over‐identifying restrictions, thus supporting the overall favorability of the liquidity‐augmented Fama–French model. In addition, we find that the asset‐pricing performance of the liquidity factor is generally very robust to a wide range of sensitivity checks.     

Nonlinear asset pricing in Chinese stock market: A deep learning approach

The redesign of asset pricing models failed to integrate the frequent financial phenomenon that stock markets exhibit a non-linear long- and short-term memory structure. The difficulty lies in developing a nonlinear pricing structure capable of depicting the memory influence of the pricing variable. This paper presents a Long- and Short-Term Memory Neural Network Model (LSTM) to capture the non-linear pricing structure among five elements in the Chinese stock market, including market portfolio return, market capitalisation, book-to-market ratio, earnings factor, and investment factor. The long–short-term memory structure implies that the autocorrelation function of the stock return series decays slowly and has a long-term characteristic. The LSTM model surpasses the standard Fama–French five-factor model in terms of out-of-sample goodness-of-fit and long–short strategy performance. The empirical findings indicate that the LSTM nonlinear model properly represents the nonlinear relationships between the five components.     

Macroeconomic risks and characteristic-based factor models

We show that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities. The factors considered include innovations in economic growth expectations, inflation, the aggregate survival probability, the term structure of interest rates, and the exchange rate. Factor mimicking portfolios constructed on the basis of book-to-market, size, and momentum therefore, serve as proxy composite macroeconomic risk factors. Conditional and unconditional cross-sectional asset pricing tests indicate that most of the macroeconomic factors considered are priced. The performance of an asset pricing model based on the macroeconomic factors is comparable to the performance of the Fama and French (1993) model. However, the momentum factor is found to contain incremental information for asset pricing.     

The high returns to low volatility stocks are actually a premium on high quality firms

Recent empirical research shows that low volatility stocks outperform high volatility stocks around the world. This study documents that the volatility effect is associated with the quality of the firm using a large sample of international stocks. First, adding a quality factor to the Fama–French model contributes to the explanation of the volatility effect. Furthermore, the negative volatility–return relation is shown to be stronger and significant only among high quality firms which are profitable and have stable cash flows. Second, a fundamental investment strategy that goes long high quality firms and short low quality firms performs like a volatility strategy and cannot be explained by common asset pricing models. However, a low–high volatility factor adds to the explanation of the return difference between high and low quality stocks as volatility and quality strategies have a common component.     

Accounting restatements and information risk

We examine the association between accounting restatements and the pricing of information risk. Using the Fama and French three-factor model augmented with discretionary and innate information risk factors, we find a significant increase in the factor loadings on the discretionary information risk factor for restatement firms after a restatement announcement. The increase in factor loadings results in an increase in the estimated cost of capital, which is cross-sectionally associated with the short-window price reaction to restatements. We study several potential determinants of the change in information risk pricing and find evidence consistent with the restatement initiator (auditor vs. firm management) and the number of times a firm restates affecting the change in the pricing of discretionary information risk. We also find an increase, of smaller magnitude, in the pricing of discretionary information risk for non-restatement firms in the same industries as the restatement firms, consistent with an information transfer effect.     

Do relative leverage and relative distress really explain size and book-to-market anomalies?

In a capital asset pricing model (CAPM) framework, Ferguson and Shockley [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] propose two factors constructed on relative leverage and relative distress, and show that the two factors subsume Fama and French's [1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56] factors constructed on size and book-to-market (BM) in explaining the cross-sectional average returns of the 25 size-BM portfolios. Based on tests on individual securities, we find that all factors fail to fully explain the common asset-pricing anomalies. In the spirit of Merton's [1973. An intertemporal capital asset pricing model. Econometrica 41, 867–887] intertemporal CAPM, we propose an augmented five-factor model, which incorporates Ferguson and Shockley's [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] factors into the Fama–French three-factor model. The empirical results show that a simple conditional version of the augmented model is able to explain most well-known asset-pricing anomalies.     

上市公司综合盈利水平与股票收益

本文基于2000-2017年上市公司的财务及股票交易数据,研究了上市公司综合盈利水平与股票收益之间的关系。我们使用目前资产定价文献中较新的偏最小二乘法和组合预测法,从12个衡量公司盈利能力的指标中提取了一个测度上市公司综合盈利水平的指标。研究结果显示,上市公司综合盈利水平能够显著预测未来股票收益。使用单因子偏最小二乘法、取12个月斜率的平均值构造的综合盈利水平最有效,以其构建的多空对冲投资组合能产生15%的年平均收益,夏普比率达到0.75。与此对应,组合预测法提取的上市公司综合盈利水平的预测能力稍低,但依然显著。在控制了其他公司特征变量后,综合盈利水平对于股票收益的解释能力依然稳健。本文还从经济机制的角度出发,探讨了综合盈利水平对收益的预测来源。我们发现,上市公司综合盈利水平与股票预期回报的正向关系在投资摩擦更低的组中更高,而在错误定价程度更高的组通常更低。这些结果支持了基于投资摩擦的Q理论,而与行为金融的错误定价理论相悖。