Size and book-to-market factors in the relationship between average stock returns and average book returns: some evidence from an emerging market

The present paper examines the association between average stock returns and average book returns and addresses the question as to whether there are common size and book-to-market factors in earnings and returns. The results of the empirical research, conducted in the Athens Stock Exchange, suggest that when the sample firms are grouped into size, book-to-market portfolios stock returns properly reflect differences in the evolution of accounting profitability. Moreover, it is found that the return on investment (ROI) measure contains size and book-to-market factors analogous to the mimic risk factors inherent in stock returns, in the sense that they capture information missed by ROI.     

Dynamic interaction of risk–return trade-offs between oil market and China’s stock market: An analysis from the risk preferences perspective

The risk–return trade-off refers to the compensation required by investors for bearing risks, which can be viewed as the risk preference of investors in a market. The current study investigates the dynamic interdependence of risk–return trade-offs between China’s stock market and the crude oil market from the perspective of risk preference of investors, which is designed to explore the transmission process of investors’ risk preference in both markets. Specifically, this study applies the time-varying parameter GARCH-M model, namely TVP-GARCH-M model, to characterize the time-dependent risk–return trade-offs (investors’ risk preferences) in the crude oil and China’s stock markets, then examines their relationship through Granger causality tests. Results show that a variation in risk preferences of the oil market investors can dramatically cause a variation in risk preferences of the Chinese stock market investors, while the risk preference of investors in the Chinese stock market does not lead to that in the crude oil market, which is in accordance with expectations. The dynamic effect of investors’ risk appetite in the crude oil market is further examined by the TVP-VAR model. The findings of this work suggest that there generally exists a positive impact of investors’ risk preference in the oil market and that the effect is time-varying to a greater degree during the short and medium term. Moreover, responses of the Chinese stock market investors’ risk preference were more significant during the 2008 financial crisis. Additionally, the empirical results remain robust when applying alternative crude oil prices and China’s stock prices.     

Effects of the fat-tail distribution on the relationship between prospect theory value and expected return

This study investigates the negative relationship between prospect theory value and expected return considering the fat-tail property of the return distribution. The results of both decile portfolio and cross-sectional regression show evidence supporting the hypothesis related to prospect theory value. However, these results are very sensitive to whether the model includes a short-term reversal factor. In the empirical design combining the hypothesis with the degree of fat-tail of the return distribution, stock groups with the fat-tail return distribution definitely show that prospect theory value has a significant information value for explaining expected return, regardless of whether the short-term reversal and other factors are included in the models. These results suggest that both the fat-tail property in the stock return distribution and the property of the skewed return distribution must be considered in examining the relationship between prospect theory value and expected return. Furthermore, our findings on the effects of the fat-tail property of the return distribution are verified through robustness testing while considering changes in empirical design and using out-of-sample stock markets of the U.S., Japan, and China, as well as the in-sample Korean stock market.     

Dispersion in analysts’ target prices and stock returns

We propose the dispersion in analysts’ target prices as a new measure of disagreement among analysts and a proxy of ex ante stock risk. In contrast to the negative return predictability of analysts’ earnings forecast dispersion but consistent with the risk hypothesis, we document a significant positive relation between the target price dispersion and future stock returns up to 24 months. The next-month return spread between the highest and lowest deciles sorted on the target price dispersion measures can be over 2%. Our findings cannot be explained by the standard risk factors and stock characteristics including the target price revision. Further supporting the risk hypothesis, the target price dispersion is positively related to future stock risk.     

Two new mean–variance enhanced index tracking models based on uncertainty theory

The enhanced index tracking (EIT) problem is concerned with selecting a tracking portfolio that achieves an excess return over a given benchmark with a minimum tracking error. This paper explores the EIT problem by providing two new mean–variance EIT models based on uncertainty theory where stock returns are treated as uncertain variables instead of random variables and stock return distributions are estimated by experts instead of from historical data. First, this paper formulates an uncertain enhanced index tracking (UEIT) model and analyzes the characteristic of the UEIT frontier. Then to reduce the tracking portfolio’s risk, this paper adds a risk index (RI) constraint to the UEIT model and proposes a UEIT-RI model. Next, by comparing the UEIT and UEIT-RI models this paper gives the advantages of the two models. Investors can choose the model according to their preferences. Finally, this paper conducts numerical examples to illustrate the application of the two models and the analysis results.     

中国股票市场风险和收益风格效应的非参数检验

本文利用Kendall协同系数检验考察我国股票市场风险和收益的风格效应。通过实证研究首次发现各风格指数的收益率、总风险及指数特有风险均具有明显的分层结构,风格效应显著。对影响风险和收益的风格因素进行的分析表明:股票风险受规模因素的影响十分明显;而股票回报率受价值因素的影响比较显著,受规模因素的影响不明显。并进一步用Spearman相关系数考察了风险与收益之间的秩相关性。本文研究结果对资产配置和风险监管等问题具有参考价值。     

Heterogenous beliefs with sentiments and asset pricing

We present a dynamic equilibrium model with two irrational investors: an extrapolator and a contrarian, whose beliefs regarding the growth rate of dividend stream are biased by their sentiments. The key contribution is to connect two disagreements with the degree of irrationality of investors and to provide novel insights into the predictability of stock return. We show that the higher level of sentiment disagreement is, the more stock price is overvalued. However, the future stock price will decline because the extrapolator’s sentiment will cool down over time. Therefore, the sentiment disagreement negatively predicts future return. At the meanwhile, our model not only shows that the survey expectations about cashflows increase the variations in asset price and dampen the corresponding volatility, but also helps to explain the mixed results about the relationship between the investors’ belief dispersions and stock return predictability.     

Disorder in the Risk Order

Abstract

This paper studies the difference in global equity portfolios allocated by the criterion of minimizing the risk by using two different risk measures, the standard deviation and the conditional value at risk. An empirical analysis is performed on a comprehensive stock exchange database. The main hypothesis of the present work is that the choice of risk measure has crucial importance in portfolio optimisation, especially in those situations when the stock markets are extremely volatile and the return distributions are non-normal. The rationale behind establishing minimum-risk portfolios is to keep track of the highest possible risk reduction benefits from international diversification.     

中国上证综合与恒生指数的风险度评估

针对中国上证综合与香港恒生指数的风险度问题,提出从风险波动的深度、广度、持久度三个方面分别进行评估,其中测量波动深度采用了VAR指标,测量波动的广度采用了极差R指标,测量风险存在的持久度采用了Hurst指数指标,综合这三方面的因素运用风险度评价指数r来评价指数的风险。选择2000年1月3日至2009年9月1日的中国上证综合与香港恒生的日收益率研究对象进行分析,结果发现：上证指数波动的深度、持久性要比恒生指数大,而波动的宽度要比恒生指数小。在本文研究期间内,上证指数的风险评价指数要比恒生指数小,这在一定程度上说明上证指数的风险度要比恒生指数小。     

Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

高阶矩波动性建模及应用

为度量高阶矩风险的动态特征、考察时变高阶矩风险对金融投资决策的影响，本文提出了一个新的高阶矩波动模型：NAGARCHSK-M模型。讨论了该模型的包容性，给出了关于高阶矩波动性建模的一整套建模技术，基于正态密度的Gram-Charlier展开给出了模型的参数估计方法。利用该模型对我国股市的高阶矩风险进行了动态描述，并讨论了时变方差风险、时变偏度风险和时变峰度风险对资产收益的影响。     

Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

Time-varying beta in functional factor models: Evidence from China

In this paper, we introduce a functional method to investigate how betas change over time in factor models. Based on the China A-share data, we drop the constant beta assumption in the CAPM and multi-factor models to estimate the time-varying betas directly from the functional data regression. The empirical results show that exposures to all risk factors have certain time-varying patterns in the Chinese A-share stock market.     

Are the profitability and investment factors valid ICAPM risk factors? Pre-1963 evidence

We empirically evaluate whether the profitability and investment factors from Novy-Marx (2013) and Fama and French (2015, 2018) are compatible with Merton’s (1973) intertemporal CAPM (ICAPM) framework in the pre-1963 period. We show that: (i) the covariance risk price estimates of the profitability factors are positive and statistically significant, which indicates that they have explanatory power with respect to the cross-section of stock returns; (ii) the investment factors carry insignificant covariance risk prices and are therefore not valid ICAPM risk factors; and (iii) the profitability factors forecast the first moment of the aggregate stock return and economic activity with the correct sign, which is consistent with their positive covariance risk price estimates and satisfies the sign restrictions associated with the ICAPM.     

Forecasting stock market volatility: Can the risk aversion measure exert an important role?

In this paper, we predict realized volatility of stock return by utilizing time-varying risk aversion based on a simple linear autoregressive model. Our in-sample results suggest that time-varying risk aversion have significant impact for stock return volatility. In terms of out-of-sample forecasting performance, the empirical results indicate that the incorporation of time-varying risk aversion in the benchmark model can yield more accurate stock return volatility forecasts. Notably, the out-of-sample forecasting results confirm that our conclusions are robust when we apply alternative lag orders and alternative prediction evaluation periods. Finally, we study links between the prediction ability of time-varying risk aversion and the volatility of other stock indices and two kinds of crude oil, and find that the new predictor can effectively strengthen forecasting performance in most case. In view of the importance of volatility risk in the asset pricing process, our research is of great significance for financial asset participants.     

Does weather impact the stock market? Empirical evidence in Taiwan

Psychological evidence suggests close relationships between weather and mood. Individuals feel in a more positive frame of mind on sunny than cloudy days. This study applies GJR–GARCH to examine the relationship among weather, stock returns and risk in Taiwan from 2001 to 2007. The empirical results indicate that precipitation does not significantly influence stock return and risk; likewise, sunshine hours and temperature insignificantly influence stock return, but do significant impact stock risk. These findings demonstrate that weather effect really exist in stock market, and can help investors in making innovative investment and management decisions.     

An economic–probabilistic model for risk analysis in technological innovation projects

This paper presents the application of an economic–probabilistic model to conduct risk analysis in technological innovation (TI) projects. The model integrates risk and economic analysis by quantifying both value and probability of occurrence of cash flow deviations, thus resulting in an economic–probabilistic analysis of the expected returns. The main risk categories and factors in TI projects are identified and associated to cash flow groups. The model allows to calculate risk-adjusted values for cash flow groups and project net present value through stochastic simulation. As a result, the model provides both the risk-adjusted project economic return with the associated probability distribution to its NPV and the variability that each risk factor generates in the project return. The model offers important benefits from the point of view of practitioners, including a condensed list of independent risk factors and the use of a monetary scale to assess risk impact which is familiar to most decision makers.     

A portfolio approach to endogenous growth: equilibrium and optimal policy

This paper develops a portfolio approach to modeling endogenous growth in continuous time that is especially suitable for addressing fiscal and financial issues in policy design. The analysis focuses on the equilibrium relationship between fiscal and financial policy, rates of return and wealth allocation. We analyze two models. The first is based on the Arrow-Romer model with increasing returns and an external effect of capital on labor productivity. The second draws on Barro's analysis of government spending and endogenous growth. In both models, we study the equilibrium allocation and discuss the optimal fiscal and financial policy.     

Forecasting risk measures using intraday data in a generalized autoregressive score framework

A new framework for the joint estimation and forecasting of dynamic value at risk (VaR) and expected shortfall (ES) is proposed by our incorporating intraday information into a generalized autoregressive score (GAS) model introduced by Patton et al., 2019 to estimate risk measures in a quantile regression set-up. We consider four intraday measures: the realized volatility at 5-min and 10-min sampling frequencies, and the overnight return incorporated into these two realized volatilities. In a forecasting study, the set of newly proposed semiparametric models are applied to four international stock market indices (S&P 500, Dow Jones Industrial Average, Nikkei 225 and FTSE 100) and are compared with a range of parametric, nonparametric and semiparametric models, including historical simulations, generalized autoregressive conditional heteroscedasticity (GARCH) models and the original GAS models. VaR and ES forecasts are backtested individually, and the joint loss function is used for comparisons. Our results show that GAS models, enhanced with the realized volatility measures, outperform the benchmark models consistently across all indices and various probability levels.     

Spillover effects in oil-related CDS markets during and after the sub-prime crisis

This paper investigates the return and volatility spillover effects across oil-related credit default swaps (CDSs), the oil market, and financial market risks for the US during and after the subprime crises. The empirical analysis is based on monthly return and realized volatility data from February 2004 to April 2020. We estimate both static and dynamic generalized dynamic spillover measures based on vector autoregressive (VAR) models. Our full sample empirical findings show that the oil market is the primary source of risk transmission for all the oil-related credit default swaps, while the bond market is the highest source of risk transmission to the stock market and vice versa. We also provide evidence that the regulated monopoly US utility sector has the least role in volatility transmission. Furthermore, the bailout program conducted by the US Treasury and Federal Reserve helped stabilize the US financial market through the purchase of toxic assets after the subprime financial crisis. We find strong evidence that the federal funds rate hike cycles lessen total risk transmission throughout the US bond market. Finally, our findings assert that oil price shocks have a significant effect on the oil-related CDSs in some sub-periods via the demand and supply transmission channels.