The Impact of COVID-19 on Stock Market in China

This paper studies the impact of the COVID-19 on the stock ambiguity, risks, liquidity, and stock prices in China stock market, before and after the outbreak of COVID-19 during the Chinese Spring Festival holidays in 2020. We measure stock ambiguity using the intraday trading data. The outbreak of COVID-19 has a significant impact on the average stock ambiguity, risk, and illiquidity in China and induces structural break in the market average ambiguity. However, the equity premium and liquidity premium change little during the same period. The market average stock ambiguity and risks decrease, and stock liquidity improves to pre-pandemic levels as the pandemic is under control in China. The market average stock ambiguity and risks in China increase again when the confirmed new cases in the U.S. surge in the second half of 2020. We also find a “flight-to-liquidity” phenomenon, and the equally-weighted (value-weighted) 20-trading-day liquidity premium declined significantly to about –4.42% (–6.48%) during the fourth quarter of 2020.

ARBITRAGEUR BEHAVIOR IN SENTIMENT-DRIVEN ASSET-PRICING

This study aims to model arbitrageur behavior in a sentiment-driven capital asset-pricing model under the premise of reflecting a more detailed decomposition of investor types in the equity markets. We explore the behavior and the impact of arbitrageur behavior, particularly, on pricing and on key financial ratios. We observe that the prevalence of the arbitrageur counteracts the effects of unsophisticated investors, resulting in a lower volatility of the price–dividend ratio, lower predictive power of changes in consumption for future price changes and lower equity premium. Thus, the results of our research allow us to conjecture that the extrapolation bias in the prices is lowered.

When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance

We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic and may be potentially disconnected. We solve a representative investor's optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Our empirical analysis shows that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from lower volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.

Predicting equity premium with adjusted dividend-price ratio: the USA and international evidence

Purpose This paper aims to achieve two main objectives. The first is to introduce a suitable adjustment to the conventional dividend-price ratio, which would address econometric concerns and improve the predictability of the equity premium. The second is to compare the predictive performance of the newly introduced adjusted dividend-price ratio with the conventional dividend-price ratio. Design/methodology/approach The authors hypothesize that the adjusted dividend-price ratio will have better predictive power and forecasting quality for equity premium compared to the conventional dividend-price ratio. To test the hypothesis, the authors predict equity premium with both variables on a sample of 11 developed and emerging market indexes over a period spanning June 1995 to March 2017. To accommodate time variation in parameter values or structural breaks in the data, the authors conducted a fixed window rolling regressions using both variables. A variety of forecast techniques including magnitude and sign accuracy measures are applied to compare the performance of forecasts. Findings The adjusted dividend-price ratio is shown to be stationary and has both lower persistence and variability compared with the conventional dividend-price ratio. The authors find that the adjusted dividend-price ratio provides superior out-of-sample (OOS) performance compared to the conventional dividend-price ratio, for both size and sign accuracy, in forecasting equity premium for the majority of the countries in the sample. Research limitations/implications This paper introduces an easy-to-follow modification in the conventional dividend-price ratio that can be replicated by researchers and practitioners alike. However, the study has a limitation in that it does not capture the impact of dividend-paying firms within each index on the predictive ability of the adjusted dividend-price ratio. Practical implications The knowledge of equity premium predictability is important in implementing market-timing strategies and could be beneficial for portfolio and risk management. The newly introduced variable is easy to construct using widely available data without the need for complex econometric estimation. Investors can use this variable to predict equity premiums in international markets, both developed and emerging. The findings of this paper will be relevant to financial analysts, portfolio managers, investors and researchers in international finance. For example, by using the adjusted dividend-price ratio, investors would see up to 0.5% improvement in their OOS monthly forecasts of the equity premium. Originality/value To the best of the authors’ knowledge, this is the first paper that proposes adjustment in the conventional dividend-price ratio based on the past observations of the most recent quarter. In this way, the paper offers fresh insight that dividend-price ratio is still useful to predict equity premium albeit, after some adjustments and modifications. The findings of the paper would result in renewed interest in using the dividend-price ratio as a predictor of the equity premium.

Equity Premium with Habits, Wealth Inequality and Background Risk

In an exchange economy with endowment inequality, we investigate how preferences with external habits affect the equity risk premium. We show that the dynamics of external additive habits with wealth inequality are complex when a background risk is present. It is ambiguous whether wealth inequality will increase or decrease the equity premium even when the income uncertainty is low. This result extends literature by suggesting that wealth inequality has a small role in explaining asset pricing puzzles.

Evolved attitudes to risk and the demand for equity

The equity premium puzzle refers to the observation that people invest far less in the stock market than is implied by measures of their risk aversion in other contexts. Here, we argue that light on this puzzle can be shed by the hypothesis that human risk attitudes were at least partly shaped by our evolutionary history. In particular, a simple evolutionary model shows that natural selection will, over the long haul, favor a greater aversion to aggregate than to idiosyncratic risk. We apply this model—via both a static model of portfolio choice and a dynamic model that allows for intertemporal tradeoffs—to show that an aversion to aggregate risk that is derived from biology may help explain the equity premium puzzle. The type of investor favored in our model would indeed invest less in equities than other common observations of risk-taking behavior from outside the stock market would imply, while engaging in reasonable tradeoffs over time.

Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?

We find that imposing economic constraint on stock return forecasts based on the Interquartile Range of equity premium can significantly strengthen predictive performance. Specifically, we construct a judgment mechanism that truncates the outliers in forecasts of stock return. We prove that our constraint approach can realize more accurate predictive information relative to the unconstraint approach from the perspective of statistics and economics. In addition, the new constraint approach can effectively defeat CT constraint and CDA strategy. The three mixed models we proposed can further enhance the accuracy of prediction, especially the mixed model combined with our constraint approach. Finally, utilizing our new constraint approach can help investors obtain considerable economic gains. With the application of extension and robustness analysis, our results are robust.