Investor heterogeneity and the cross-sectional stock returns in China

We examine the relationship between divergence of opinion and the cross-sectional stock returns in Chinese A share market where short-selling of stocks is prohibited by law. Using a proxy for divergence of opinion among the entire investor base, we document a positive relationship between divergent beliefs and future stock returns. This is in sharp contrast to Miller's (1977) prediction of a negative relationship between the two. The result is likely to be driven by the dominance of individual investors and their speculative trading behaviors in China. Miller's prediction is confirmed when divergence of opinion is measured using data on mutual fund holdings. Our results are robust to a number of common return predictors. We also find a significantly negative relationship between the fraction of tradable shares in listed Chinese companies and future stock returns. Increase in the fraction of tradable shares tends to reduce the predictability of stock returns using divergence of opinion.

Determinants of stock returns: Factors or systematic co-moments? Crisis versus non-crisis periods

In this paper we evaluate the intertemporal pricing performance of stock return determinants over the periods surrounding, and outside of, financial crises. The analysis focuses on the variables of size, book-to-market ratio, momentum, liquidity, and higher-order systematic co-moments. The evidence reveals that over non-crisis periods the market beta plays an important role in determining the cross-section of stock returns. Size, value, momentum, and liquidity also exhibit associations with the cross-section of stock returns. However, over crisis periods most of the variables we examined lose their explanatory power, suggesting that their usefulness is limited for investment purposes when financial markets experience crises. There is some evidence of coskewness pricing surrounding market crashes. Practitioners may consider coskewness over crisis periods.

Three essays on stock returns and inflation - Australian evidence

Results of this thesis suggest that a significant negative relation between stock returns and inflation identified in Australia during ‘inflation targeting’ is mainly due to an incidence of ‘flight to safety’. Furthermore, the impact of inflation news on stock returns is industry-sector dependent. Specifically, in Australia rising inflation seems to be good news for Financials, but bad news for Materials.

Has oil price predicted stock returns for over a century?

This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150. years (1859:10-2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroscedasticity. Three key findings are unraveled: first, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.

Oil price and stock returns of consumers and producers of crude oil

In this paper we investigate how differently stock returns of oil producers and oil consumers are affected from oil price changes. We find that stock returns of oil producers are affected positively by oil price changes regardless of whether oil price is increasing or decreasing. For oil consumers, oil price changes do not affect all consumer sub-sectors and where it does, this effect is heterogeneous. We find that oil price returns have an asymmetric effect on stock returns for most sub-sectors. We devise simple trading strategies and find that while both consumers and producers of oil can make statistically significant profits, investors in oil producer sectors make relatively more profits than investors in oil consumer sectors.

Non-tradable share reform, liquidity, and stock returns in China

This article studies the influence of the non-tradable share reform in the cross-section of stock returns in China. Prior research has generally neglected this important development in the Chinese stock market. We find that the firm-specific illiquidity measures that reflect direct transaction costs, price impact and difficulties in trading immediacy, exhibit a positive and significant relationship with stock returns. These effects are particularly pronounced after the non-tradable share reform. Furthermore, in the post-reform era, portfolios with high illiquidity (i.e. high relative bid-ask spread, high Amihud illiquidity, low Amivest liquidity ratio) significantly outperform portfolios with low illiquidity, controlling for size, and book-to-market effects.

Studies of firm efficiency on stock returns

 The thesis provides strong evidence for a negative relationship between firm efficiency and average stock returns in the Australian market. Moreover, the findings indicate that the return anomalies are more likely due to mispricing in which arbitrage costs play an important role in explaining the efficiency effect.

The relationship between stock returns and the foreign exchange rate: the ARDL approach

This study employs the ARDL cointegration approach in order to examine the impact
of financial liberalization on the relationships between the exchange rate and share
market performance in China. We discovered that cointegration has existed between the
Shanghai A Share Index and the exchange rate of the renminbi against the US dollar
and Hong Kong dollar since 2005, when the Chinese exchange rate regime became a
flexible, managed, floating system. We found that both the exchange rate and the money
supply influenced stock price, with a positive correlation. We further show that the
money supply increase was largely caused by a huge ‘hot money’ inflow from other
countries in recent years. After local currency appreciation, hot money, followed by
the money supply increase, pushed the market into a high level, based on expectations
regarding the local currency’s further appreciation.

Do order imbalances predict Chinese stock returns? New evidence from intraday data

In this paper we examine whether order imbalances can predict the Chinese stock market returns. We use intraday data, a panel data predictive regression model that accounts for persistent and endogenous order imbalances and cross-sectional dependence in returns, and show that order imbalances predict stock returns from 1-minute trading to 90-minute trading. On the basis of this predictability evidence using multiple trading strategies we show that profits persist during the day. These results imply that a source of Chinese market inefficiency is order imbalances.

Are Indian stock returns predictable?

In this paper we show that Indian stock returns, based on industry portfolios, portfolios sorted on book-to-market, and on size, are predictable. While we discover that this predictability holds both in in-sample and out-of-sample tests, predictability is not homogenous. Some predictors are important than others and some industries and portfolios of stocks are more predictable and, therefore, more profitable than others. We also discover that a mean combination forecast approach delivers significant out-of-sample performance. Our results survive a battery of robustness tests.

A random coefficient approach to the predictability of stock returns in panels

© The Author, 2014. Most studies of the predictability of returns are based on time series data, and whenever panel data are used, the testing is almost always conducted in an unrestricted unit-by-unit fashion, which makes for a very heavy parametrization of the model. On the other hand, the few panel tests that exist are too restrictive in the sense that they are based on homogeneity assumptions that might not be true. As a response to this, the current study proposes new predictability tests in the context of a random coefficient panel data model, in which the null of no predictability corresponds to the joint restriction that the predictive slope has zero mean and variance. The tests are applied to a large panel of stocks listed at the New York Stock Exchange. The results suggest that while the predictive slopes tend to average to zero, in case of book-to-market and cash flow-to-price the variance of the slopes is positive, which we take as evidence of predictability.