Forecasting equity returns: The role of commodity futures along the supply chain

This paper examines equity return predictability using the returns of commodity futures along the supply chain in China's financial market. We find that a considerable number of commodities exhibit significant in‐sample forecasting ability at the daily horizon, especially for supplier‐side equity returns. The macroeconomic risk premium effect, captured by the aggregate commodity prices, is an important source for this predictability. The out‐of‐sample results show that for most commodities, the predictability remains both statistically and economically significant, and the forecasting performance improves substantially during recessions or with economic constraints.     

The response of volume and returns to the information shocks in China's commodity futures markets

This study investigates the response of returns and volume to different information shocks in China's commodity futures markets using bivariate moving average representation (BMAR) and bivariate vector autoregression (BVAR) methodologies. Consistent with the conclusions from stock market studies that have used these methodologies, it is found that the informational/permanent components are the dominant components for returns movements, and the noninformational/transitory components are the dominant components for trading volume. It is also found that the market response of copper futures improved during the sample period, and the market responses of actively traded futures (copper and soybeans) are better than those of the less actively traded futures (aluminum and wheat). © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:893–916, 2005     

Stock return predictability of the cumulative abnormal returns around the earnings announcement date: Evidence from China

We find that cumulative abnormal returns adjusted by size, book-to-market, and momentum around the earnings announcement date (DGTW_CAR3 hereafter) significantly and positively predict stock returns in the 6-month period from May 2005 to October 2020 in the China's A-shares market. The monthly equally-weighted DGTW_CAR3 premiums are 0.47% and 0.67% after risk adjustment. Although stock price delay fails to fully account for the DGTW_CAR3 premium, we find that the DGTW_CAR3 premium is more significant for illiquid stocks and during periods with high investor sentiment. This result suggests that market inefficiency explains the DGTW_CAR3 premium. Further analysis shows that, in addition to earnings information, the optimism reflected in the management discussion and analysis section of the annual or half-year report also contributes to the DGTW_CAR3 premium. This finding implies that DGTW_CAR3 may contain new fundamental information that correlates significantly and positively with future stock performance. Finally, we find that the institutional ownership change of a stock associated with DGTW_CAR3 also significantly and positively predicts the stock's return, suggesting that institutional investors adjust their holdings according to DGTW_CAR3 and consequently influence the demand for the stock in the China's A-shares market.     

Commodity momentum decomposition

This study decomposes the momentum factor (MOM) in the commodity futures market. A high-to-price (HTP) factor generates a higher Sharpe ratio than a price-to-high (PTH) factor. We uncover that the profitability mechanisms across three momentum factors are different. The positive returns on MOM and PTH are associated with overconfidence and strong self-attribution. In contrast, HTP is linked to investors' underreaction and the information diffusion process. Moreover, we find that positive demand shocks raise the return on HTP.     

Intraday time-series momentum: Evidence from China

This study conducts an investigation of intraday time-series momentum across four Chinese commodity futures contracts: copper, steel, soybean, and soybean meal. Our results indicate that the first half-hour return positively predicts the last half-hour return across all four futures. Furthermore, in metals markets, we find that first trading sessions with high volume or volatility are associated with the strongest intraday time-series momentum dynamics. Based on this, we propose an intraday momentum informed trading strategy that earns a return in excess of standard always long and buy-and-hold benchmarks.     

How about selling commodity futures losers?

This paper explores the benefits of extending the investment universe to commodity futures, from the perspective of momentum traders. We find that the growth-optimal portfolio includes negative (positive) weights on commodity futures losers (stock winners). Motivated by this finding, we construct a joint momentum strategy, buying stock winners and selling commodity futures losers, and show that it generates an average monthly return of up to 1.91% and provides much lower skewness (0.04) and kurtosis (1.27) than a traditional stock momentum strategy. It also greatly improves profitability, especially in unfavorable market states, and thus effectively manages tail risk.     

The quantile dependence of commodity futures markets on news sentiment

Focusing on energy commodities, industrial metals, and gold, this paper examines the degree to which commodity futures returns depend on news sentiment under various market conditions, and the structure of that dependence. We observe an asymmetric market reaction to positive and negative news sentiment, which changes in periods of financial turmoil. The quantile regression analysis shows that news sentiment's influence on the futures returns follows an upward trend at higher percentiles. This structure flattens for positive news during the global financial crisis, while the slope for the negative component steepens in backwardation periods.     

Market quality and the connectedness of steel rebar and other industrial metal futures in China

We examine the market quality of China's steel rebar futures, along with three other important industrial metal futures. Steel rebar futures are the most active metal futures contracts in China. Our analyses show that while steel rebar and copper futures are comparable in terms of informational efficiency, they are more informationally efficient than iron ore and aluminum futures, with low bid–ask spread, volatility persistence, pricing error variance, and probability of informed trading. We find a bidirectional connection between iron ore and steel rebar futures. Furthermore, we show that these metal futures are weakly related to the Chinese stock market.     

The role of financial investors in determining the commodity futures risk premium

I develop and test a model to study the interaction between the commodity and stock markets. This study attempts to clarify the debate about the effect of financialization on commodity markets. Theoretically, the futures risk premium is determined by hedging pressure, stock market returns, and the commodity–equity correlation. Empirically, the effect of the stock market on the energy market became significantly greater for the futures risk premium in the period following the 2008 crisis. Furthermore, hedging pressure is a strong explanatory variable for the futures risk premium in various circumstances.     

The market quality of commodity futures markets

To study the market quality of commodity futures markets, we construct a commodity futures market quality index from the perspective of liquidity, efficiency, and volatility. Based on the market quality index, the Chinese commodity futures market operates steadily. The metal futures market is more efficient and stable than the market for agricultural futures. The Chinese commodity futures market is less liquid and more volatile than the U.S. market. We examine the determinants of market quality and find that macroeconomic variables and futures market contracts are significantly related to the market quality of Chinese commodity futures.     

Valuation of futures and commodity options with information costs

In this article, futures and commodity options are analyzed in the context of Merton's (1987) model of capital market equilibrium with incomplete information. First, following Dusak (1973) and Black (1976), the conditions under which Merton's model can be applied to the valuation of forward and futures contracts are proposed. Then an application to futures markets is given. We provide a partial differential equation and the formulas for European commodity options, futures contracts, and American options in the same context. The models are simulated and compared to standard models with no information costs. We find that model prices are not significantly different from standard model prices. However, our models correct for some pricing biases in standard models. In particular, they reduce the overvaluation bias for European and American commodity options. It seems that the costs of gathering and processing information regarding the option and its underlying asset play a role in explaining the biases observed in standard models. This work can be applied to other futures markets. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 645–664, 1999     

Efficient use of commodity futures in diversified portfolios

We provide evidence on the role of commodity futures in portfolios comprised of stocks, bonds, T‐bills, and real estate. Over the period investigated (1973–1997), Markowitz optimization over a range of risk levels gives substantial weight to commodity futures, thereby enhancing the portfolios’ returns. We find dramatically different results when we use a simple ex ante measure of monetary stringency to dichotomize the sample into expansive‐versus‐restrictive monetary‐policy periods. In periods characterized by restrictive monetary policy, commodity futures are shown to have substantial weight in the efficient portfolios, with significant return enhancement at all levels of risk. In periods characterized by expansive monetary policy, commodity futures are shown to have little or no weight in the efficient portfolios, with no return enhancement at all levels of risk. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:489–506, 2000     

Do country risk and financial uncertainty matter for energy commodity futures?

Using an instrumental variable quantile regression technique, this paper assesses whether country risk and financial uncertainty exert an impact on energy commodity futures prices under different commodity conditional return distributions over the period from January 1994 to July 2017. We also discuss whether the correlations change with different dimensions of country risk, that is economic, financial, and political. The results reveal that country risk and financial stress do have a significant impact on energy commodity returns of futures contracts with different maturities, but their direction, intensity, and significance differ, caused by the distinct market situations and divergent channels of country risk.     

CEO turnover,political connections,and firm performance: Evidence from China

In our analysis of 5738 CEO turnover events among A-share listed companies in China over the period of 1993 to 2019, we find that CEO turnovers on average hurt companies' market performance with significant negative abnormal returns in the event window. We then group the companies into four types based on whether the outgoing and successor CEOs have political connections, and then calculate the abnormal returns in the event windows of CEO turnovers once announced. We find that companies generally enjoy positive abnormal returns if they replace politically non-connected CEOs with connected ones. Such a positive effect is more evident among non-state-owned enterprises (non-SOEs), companies with worse performance, and companies with higher financial constraints. However, abnormal returns derived from hiring politically connected successor CEOs turn to negative following China's massive anti-corruption campaign in 2012. Our findings provide direct estimations of the economic value of CEOs' political connections for A-share listed companies in China and reveal boundary conditions that moderate the influence of hiring politically connected CEOs.     

Intermediary asset pricing in commodity futures returns

This paper assesses the extent to which intermediary capital (IC) risk contributes toward explaining commodity futures returns. We find that the IC effect is substantially positive and continues to grow as the financialization of commodities deepens. Positive and negative IC risks play asymmetric roles, with the effect of negative IC strengthening in recent subperiods. We further confirm the heterogeneous roles of IC across individual commodities by cross-section analyses. Overall, the effect of the positive IC risk factor varies significantly. Portfolios with low basis, low open interest, low momentum, and low liquidity earn significantly higher returns than counterparty portfolios.     

Cross‐market correlations and transmission of information

We investigate characteristics of cross‐market correlations using daily data from U.S. stock, bond, money, and currency futures markets using a new multivariate GARCH model that permits direct hypothesis testing on conditional correlations. We find evidence that arrival of information in a market affects subsequent cross‐market conditional correlations in the sample period following the stock market crash of 1987, but there is little evidence of such a relationship in the precrash period. In the postcrash period, we also find evidence that the prime rate of interest affects daily correlations between futures returns. Furthermore, we find that conditional correlations between currency futures and other markets decline steeply a few months before the crash and revert to normal dynamics after the crash. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:1059–1082, 2002     

Impact of international energy prices on China's industries

This study examines how returns and volatility of future contracts for Brent crude oil (Brent), West Texas Intermediate crude oil (WTI), Henry Hub natural gas, and Newcastle thermal coal impacts industries in China. Using the firm-level data of 3,750 stock listings across both Shanghai and Shenzhen stock exchanges, segregated into 138 subindustries under the Global Industry Classification Standard, this study finds evidence that crude oil futures have the most significant influence. Further analysis suggests that stock returns of oil-related companies are more closely align to Brent and WTI's futures returns following China's key oil pricing reform on March 27, 2013. Overall, Chinese industries are also more exposed to global crude oil futures volatility after this event.     

A cointegrated commodity pricing model

We propose a commodity pricing model that extends the Gibson–Schwartz two‐factor model to incorporate the effect of linear relations among commodity spot prices, and provide a condition under which such linear relations represent cointegration. We derive futures and call option prices for the proposed model, and indicate that, unlike in Duan and Pliska (2004), the linear relations among commodity prices should affect commodity derivative prices, even when the volatilities of commodity returns are constant. Using crude oil and heating oil market data, we estimate the model and apply the results to the hedging of long‐term futures using short‐term ones.     

The impact of the US stock market opening on price discovery of government bond futures

We examine price discovery in sequential markets for the 10-year US Treasury note, German bund, and UK gilt futures over the period 2010–2017. We find that price discovery increases after the opening of the US stock market. Order flows in the bond futures markets are more informative for permanent price changes in the 30-min period after the US stock market opens. A placebo test using US statutory holidays confirms our findings. A cross-market analysis suggests that the increased price discovery in the bond futures is related to returns and net order flows of the US stock market.     

Can night trading reduce price volatility? Evidence from China's corn and corn starch futures markets

Since 2013, China's futures exchanges have implemented night trading for agricultural futures to reduce the overnight risk and price jump of futures products by extending trading hours. This study uses difference-in-differences (DID) to examine the impacts of night trading on daytime price volatility in corn and corn starch futures markets. On the basis of tick-by-tick data for these futures, we find that night trading has significantly reduced daytime volatility and contributed to price volatility stability in the corresponding futures market. Moreover, we make DID estimations for separate daytime sessions and find that the reduction of the daytime volatility takes place mainly during the first trading session. Robustness and placebo tests further support our main conclusions. Our results provide valuable guidance for futures exchanges and regulators seeking to formulate night trading policies for futures and options.