Is default risk the hidden factor in momentum returns? Some empirical results

This paper analyzes the role of default risk in the momentum effect focusing on data from four developed European stock markets (France, Germany, Spain and the United Kingdom). Using a market‐based measure of default risk, we show that it is not the hidden factor behind this effect. While the loser portfolio is characterized by high default risk, small size, high book‐to‐market and illiquidity, characterization of the winner portfolio is somewhat more complex. Given that the momentum strategy is the return differential between the winners and the losers, factors such as the stock market cycle or the evolution of momentum portfolios against their reference point make momentum profits difficult to forecast.     

基于时间序列极值理论的跳跃风险研究

金融资产的跳跃行为作为对极端事件的刻画,为研究极端事件风险提供了良好工具。基于时间序列下的极值理论,在放松独立同分布假设下,构造了金融资产收益率序列尾部中跳跃动态特征的极值模型。通过对上证综指大跨度、高频度的实证研究,剖析了投资者结构、投资者行为与收益尾部分布之间的相互作用机制,进一步对金融资产收益尾部的跳跃风险进行了有效测度。结果表明,极端跳跃风险的分布特征在频率与尾部方向上呈现很强的不对称状态。     

A simple indicator of systemic risk

We examine the relevance and effectiveness of stock return correlations among financial institutions as an indicator of systemic risk. By analyzing the trends and fluctuations of daily stock return correlations and default correlations among the 22 largest bank holding companies and investment banks from 1988 to 2008, we find that daily stock return correlation is a simple, robust, forward-looking, and timely systemic risk indicator. There is an increasing trend in stock return correlation among banks, whereas there is no obvious correlation trend among non-banks. We also disaggregate the stock returns into systematic and idiosyncratic components and find that the correlation increases are largely driven by the increases in correlations between banks’ idiosyncratic risks, which give rise to increasing systemic risk. Correlation spikes tend to predict or coincide with significant economic or market events, especially during the 2007–2008 financial crisis. Furthermore, we show that stock return correlations offer a perspective on the level of systemic risk in the financial sector that is not already captured by default correlations. Stock return correlations are not subject to data limitations or model specification errors that other potential systemic risk measures may face. Therefore, we recommend that regulators and businesses monitor daily stock return correlations among those large and highly leveraged financial institutions to track the level of systemic risk.     

Fundamental Drivers of Dependence in REIT Returns

We analyse the empirical relationships between firm fundamentals and the dependence structure between individual REIT and stock market returns. In contrast to previous studies, we distinguish between the average systematic risk of REITs and their asymmetric risk in the sense of a disproportionate likelihood of joint negative return clusters between REITs and the stock market. We find that REITs with low systematic risk are typically small, with low short-term momentum, low turnover, high growth opportunities and strong long-term momentum. Holding systematic risk constant, the main driving forces of asymmetric risk are leverage and, to some extent, short-term momentum. Specifically, we find that leverage has an asymmetric effect on REIT return dependence that outweighs the extent to which it increases the average sensitivity of REIT equity to market fluctuations, explaining the strong negative impact of leverage on firm performance especially during crisis periods that has been documented in recent empirical work.     

Jump risk,stock returns,and slope of implied volatility smile

In the presence of jump risk, expected stock return is a function of the average jump size, which can be proxied by the slope of option implied volatility smile. This implies a negative predictive relation between the slope of implied volatility smile and stock return. For more than four thousand stocks ranked by slope during 1996–2005, the difference between the risk-adjusted average returns of the lowest and highest quintile portfolios is 1.9% per month. Although both the systematic and idiosyncratic components of slope are priced, the idiosyncratic component dominates the systematic component in explaining the return predictability of slope. The findings are robust after controlling for stock characteristics such as size, book-to-market, leverage, volatility, skewness, and volume. Furthermore, the results cannot be explained by alternative measures of steepness of implied volatility smile in previous studies.     

Overconfidence among option traders

The investor overconfidence theory predicts a direct relationship between market‐wide turnover and lagged market return. However, previous research has examined this prediction in the equity market, we focus on trading in the options market. Controlling for stock market cross‐sectional volatility, stock idiosyncratic risk, and option market volatility, we find that option trading turnover is positively related to past stock market return. In addition, call option turnover and call to put ratio are also positively associated with the past stock market return. These findings are consistent with the overconfidence theory. We also find that overconfident investors trade more in the options market than in the equity market. We rule out explanations other than investor overconfidence, such as momentum trading and varying risk preferences, for our findings.     

Momentum spillover from stocks to corporate bonds

We investigate and improve momentum spillover from stocks to corporate bonds, i.e. the phenomenon that past winners in the equity market are future winners in the corporate bond market. We find that a momentum spillover strategy exhibits strong structural and time-varying default risk exposures that cause a drag on the profitability of the strategy and lead to large drawdowns if the market cycle turns from a bear to a bull market. By ranking companies on their firm-specific equity return, instead of their total equity return, the default risk exposures halve, the Sharpe ratio doubles and the drawdowns are substantially reduced.     

南橘北枳:A股市场的经济关联与股票回报

本文系统检验并比较了中国A股市场中行业动量、区域动量、供应链动量以及科技关联动量等经济关联动量的显著性及预测周期。本文发现,中国股票市场中经济关联因子呈现出与美国股票市场不同的规律,在月度层面行业动量显著,而科技关联因子只在周度上具有显著的预测能力。进一步分析科技关联动量发现,中国股票市场中科技关联因子能预测目标公司未来1-3周的股票收益和未来基本面的变化,据此构建的多空策略能够产生周度0.16%的超额收益(年化8.67%);机制检验发现,科技关联因子预测期短的原因是由于中国股票市场中存在较多具有博彩倾向的散户投资者;有限注意和市场摩擦两个机制检验证明科技关联动量源自错误定价。进一步检验发现,科技关联动量在国有企业和创新政策颁布后更加显著。本文补充了现有A股市场的动量研究,有助于理解中国股票市场规律、提升资本市场有效性。     

Corporate bond default risk: A 150-year perspective

We study corporate bond default rates using an extensive new data set spanning the 1866-2008 period. We find that the corporate bond market has repeatedly suffered clustered default events much worse than those experienced during the Great Depression. For example, during the railroad crisis of 1873-1875, total defaults amounted to 36% of the par value of the entire corporate bond market. Using a regime-switching model, we examine the extent to which default rates can be forecast by financial and macroeconomic variables. We find that stock returns, stock return volatility, and changes in GDP are strong predictors of default rates. Surprisingly, however, credit spreads are not. Over the long term, credit spreads are roughly twice as large as default losses, resulting in an average credit risk premium of about 80 basis points. We also find that credit spreads do not adjust in response to realized default rates.     

Up and down together? On the linkage of momentum and reversal

This paper presents evidence of momentum and reversal being related phenomena in the German stock market. This finding contrasts Conrad and Yavuz's (2017) results for the US stock market. In the German stock market, the linkage of both phenomena is documented to be more pronounced after the turn of the millennium. In particular, low-risk stocks produce momentum, and high-risk stocks generate return reversal in momentum portfolios. Short-run momentum is consistently generated by the long winner leg, whereas long-run return reversal is due to the short loser leg of long-short portfolios in the German stock market.     

Market liquidity risk factor and financial market anomalies: Evidence from the Chinese stock market

The Chinese stock market is an order-driven market and hence its characteristics are structurally different from quote-driven markets. There are no studies that consider the role of the market liquidity risk factor in determining cross-sectional stock returns in a model including financial market anomalies for order-driven markets. Our aim is to test whether financial market anomalies such as firm size, the book-to-market ratio, the turnover rate, and momentum both with and without the inclusion of the market liquidity risk factor in the case of the Chinese stock market can explain cross-sectional stock returns. The empirical framework is based on the model proposed by Avramov and Chordia (AC, 2006). Our main finding is that the AC model can capture financial market anomalies except momentum when we include the market liquidity risk factor on the Chinese stock market.     

MACROECONOMIC VARIABLES AND SEASONAL MEAN REVERSION IN STOCK RETURNS

In this paper I investigate whether seasonal mean reversion in stock portfolio returns is related to common macroeconomic risk factors. I decompose excess returns into explained and unexplained returns using a multifactor pricing model. The explained excess returns exhibit January mean reversion; the unexplained excess returns do not. The mean reversion can be attributed to the components of return related to unexpected inflation, bond default premium, and market risk. The results do not depend on the time-series properties of the portfolio betas. Bond default premia and excess market returns are mean reverting in January.     

Size,value and momentum in stock returns: evidence from India

This paper examines the effects of size, value and momentum on the cross-sectional relation between expected returns and risk in the Indian stock market. We find that the conditional Carhart four-factor model empirically describes the variation of cross-section of return better than the unconditional model. When size, book-to-market and momentum effects are controlled in the conditional model, the positive relation of market beta, book-to-market and momentum with expected returns remains economically and statistically significant. However, this evidence is found to be subject to characteristics of test portfolios. The expected returns are sensitive to changes in predictive macroeconomic variables.     

Permanent and Transitory Components in the Chinese Stock Market: The ARJI-Trend Model

This study applies the ARJI-trend model in conjunction with the procedure proposed by Bai and Perron (2003) to investigate the coexistence of permanent and transitory components and time-varying jumps in the A and B stock market indices of the Shanghai and Shenzhen Stock Exchanges. Although the response to outside innovations is greater within the transitory component, it is short-lived; conversely, though there is a high level of persistence in the trend, new information has only a lesser effect on the permanent component. Jump variance can also affect total variance, though the effect is far lower than the variance for generalized autoregressive conditional heteroskedasticity. Accordingly, the market risk appears small. The reaction to news is heterogeneous within the Shanghai and Shenzhen indices; this may be the result of various market characteristics. During event periods, the permanent component, transitory components, and jump intensity are larger than their averages. After an upward trend, markets return to regular conditions over time. In sum, the total long-run risks within China's market seem low, though speculators can use the sizable transitory component of market fluctuation to engage in arbitrage activities. However, from the viewpoint of asset allocation regarding the trading noise in the Shenzhen B market, we suggest that rational investors deploy more funds in this market and less in the Shanghai A market to avoid a high degree of risk.     

Market skewness risk and the cross section of stock returns

The cross section of stock returns has substantial exposure to risk captured by higher moments of market returns. We estimate these moments from daily Standard & Poor's 500 index option data. The resulting time series of factors are genuinely conditional and forward-looking. Stocks with high exposure to innovations in implied market skewness exhibit low returns on average. The results are robust to various permutations of the empirical setup. The market skewness risk premium is statistically and economically significant and cannot be explained by other common risk factors such as the market excess return or the size, book-to-market, momentum, and market volatility factors, or by firm characteristics.     

Earning the right premium on the right factor in portfolio planning

The optimal portfolio as well as the utility from trading stocks and derivatives depends on the risk factors and on their market prices of risk. We analyze this dependence for a CRRA investor in models with stochastic volatility, jumps in the stock price, and jumps in volatility. We find that the compartment of the total variance into diffusion risk and jump risk has a small impact on the utility in an incomplete market only. In contrast, the decomposition of the equity risk premium into a diffusion component and a jump risk component and the compartment of the latter into its various elements has a huge impact on the utility in a complete market. The more extreme the market prices of risk, i.e. the more they deviate from their equilibrium values, the larger the utility of the investor. Additionally, we show that the structure of the optimal exposures to jump risk crucially depends on which elements of jump risk are priced.     

The Book-to-Price Effect in Stock Returns: Accounting for Leverage

This paper lays out a decomposition of book‐to‐price (B/P) that derives from the accounting for book value and that articulates precisely how B/P “absorbs” leverage. The B/P ratio can be decomposed into an enterprise book‐to‐price (that pertains to operations and potentially reflects operating risk) and a leverage component (that reflects financing risk). The empirical analysis shows that the enterprise book‐to‐price ratio is positively related to subsequent stock returns but, conditional upon the enterprise book‐to‐price, the leverage component of B/P is negatively associated with future stock returns. Further, both enterprise book‐to‐price and leverage explain returns over those associated with Fama and French nominated factors—including the book‐to‐price factor—albeit negatively so for leverage. The seemingly perverse finding with respect to the leverage component of B/P survives under controls for size, estimated beta, return volatility, momentum, and default risk.     

中美可转换债券比较研究

通过对中国和美国的可转换债券市场的规模、条款、风险收益特征和套利机会进行对比分析,结果表明中国可转债市场规模仍远不及美国,尤其对创新性中小企业融资需求的支持上差距更大。中国可转债的条款设计更多替发行人考虑,而较少关注投资者的需求,具有明显的扩股融资动机。从风险收益特征和套利机会来看,发现美国可转换债券市场的债性凸显,股性较弱,而中国可转换债券市场具有偏股性。     

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.