Intraday momentum in Chinese commodity futures markets

In this paper, we study whether the intraday momentum exists in Chinese commodity futures markets. We first construct an open-interest-weighted index with the high-frequency data of all commodity futures traded and then examine the predictability of the last half-hour return with both in-sample and out-of-sample tests. Consistent with findings in other markets, we show that the first half-hour return can readily predict the last half-hour return. We further demonstrate that the magnitude of this intraday momentum varies with volatility, trading volume, trade size, the sign of the first half-hour return, the type of commodity futures, and the launch of night trading. Additionally, this intraday momentum does not result from data snooping but has economic significance and remains robust under different index weighting and predictor calculation methods.     

Exploiting commodity momentum along the futures curves

This study examines novel momentum strategies in commodities futures markets that incorporate term-structure information. We show that momentum strategies that invest in contracts on the futures curve with the largest expected roll-yield or the strongest momentum earn significantly higher risk-adjusted returns than a traditional momentum strategy, which only invests in the nearest contracts. Moreover, when incorporating conservative transaction costs we observe that our low-turnover momentum strategy more than doubles the net return compared to a traditional momentum strategy.     

Financialization and speculators risk premia in commodity futures markets

J.M. Keynes coined the term normal backwardation, a situation where a futures price for a particular expiry month is less than the expected spot price for that month. He argued hedgers pay speculators a risk premium, giving rise to normal backwardation. We study the behavior of commodity futures before and since financialization of the markets, which started about 20 years ago. We find the poor returns to managed futures in recent years are likely due to the impact of financialization and the associated outside money suppressing the futures risk premium.     

Tactical allocation in commodity futures markets: Combining momentum and term structure signals

This paper examines the combined role of momentum and term structure signals for the design of profitable trading strategies in commodity futures markets. With significant annualized alphas of 10.14% and 12.66%, respectively, the momentum and term structure strategies appear profitable when implemented individually. With an abnormal return of 21.02%, our double-sort strategy that exploits both momentum and term structure signals clearly outperforms the single-sort strategies. This double-sort strategy can additionally be utilized as a portfolio diversification tool. The abnormal performance of the combined portfolios cannot be explained by a lack of liquidity, data mining or transaction costs.     

Explain systemic risk of commodity futures market by dynamic network

Since inflation of commodities is becoming more and more severe recently caused by many macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity futures market is getting more attention from academic and industrial areas. Instead of using external factors to explain this risk as previous researches, we explain it by internal topology and structures of commodity futures market. This method helps us understand its key driving factors and their different impact to Chinese and international commodity futures markets.     

Market sentiment in commodity futures returns

We identify a strong presence of sentiment exposure in commodity futures returns. Sentiment is able to provide additional explanatory power for comovement among commodity futures beyond the macro- and equity-related sources. Commodity futures with low open interest growth, high volatilities, low momentum, or low futures basis are more sensitive to change in sentiment. Similar to Baker and Wurgler (2006), we construct a market sentiment index by Partial Least Squares regressions (PLS) with non-return based stock market proxies, in particular higher moments of the option implied return distribution. Moreover, our sentiment index can be built on a daily basis.     

Momentum strategies in commodity futures markets

The article tests for the presence of short-term continuation and long-term reversal in commodity futures prices. While contrarian strategies do not work, the article identifies 13 profitable momentum strategies that generate 9.38% average return a year. A closer analysis of the constituents of the long–short portfolios reveals that the momentum strategies buy backwardated contracts and sell contangoed contracts. The correlation between the momentum returns and the returns of traditional asset classes is also found to be low, making the commodity-based relative-strength portfolios excellent candidates for inclusion in well-diversified portfolios.     

Direction-of-change forecasting in commodity futures markets

This paper examines direction-of-change predictability in commodity futures markets using a variety of binary probabilistic techniques. As well as traditional techniques, we apply Variable Length Markov Chain (VLMC) analysis, an innovative technique popularised in computational biology when predicting DNA sequences (Bühlmann & Wyner, 1999). To the best of our knowledge, this is the first application of VLMC in finance. Our results show that both VLMC and technical analysis methods provide strong predictability of the direction-of-change of commodity returns, with annualised mean returns of approximately 8%, substantially higher than the passive long strategy. Our results suggest that a short-term learning effect is present in commodities market which can be exploited using innovative direction-of-change forecasting techniques.     

Optimal portfolios in commodity futures markets

We develop a general approach to portfolio optimization in futures markets. Following the Heath–Jarrow–Morton (HJM) approach, we model the entire futures price curve at once as a solution of a stochastic partial differential equation. We also develop a general formalism to handle portfolios of futures contracts. In the portfolio optimization problem, the agent invests in futures contracts and a risk-free asset, and her objective is to maximize the utility from final wealth. In order to capture self-consistent futures price dynamics, we study a class of futures price curve models which admit a finite-dimensional realization. More precisely, we establish conditions under which the futures price dynamics can be realized in finite dimensions. Using the finite-dimensional realization, we derive a finite-dimensional form of the portfolio optimization problem and study its solution. We also give an economic interpretation of the coordinate process driving the finite-dimensional realization.     

Return and volatility co-movement in commodity futures markets: the effects of liquidity risk

Commodity markets are a widely researched topic in the field of finance. In this paper, we investigate the co-movement of return and volatility measures in different commodity futures markets and how these measures are affected by liquidity risk. First, we find that commodity returns display co-movement and that liquidity risk plays a key role in shaping asset return patterns. Moreover, we show that the volatilities of commodity returns co-move, and we demonstrate the role of liquidity risk in this joint pattern. We also find that the commodity markets we investigated share a common volatility factor that determines their joint volatility co-movement. Because liquidity risk affects both commodity returns and volatility shocks, it might be interpreted as the common causal factor driving both measures simultaneously. Therefore, we affirm the view that liquidity shocks are firmly related to two residual risks originating from both market return and market volatility. Finally, we also show that liquidity spillovers can significantly drive cross-sectional correlation dynamics.     

Including commodity futures in asset allocation in China

In this paper, we investigate the role of eight commodity futures in asset allocation in China during the period January 2004–December 2015. The Chinese commodities and stocks are moderately correlated. We use quantile regressions based on a value-at-risk model to examine the relation between these two markets. We find no risk spillovers between the markets, suggesting that stocks and commodities in China are exposed to different risks. Using different asset allocation strategies, we show that including soymeal and soybeans in the Chinese stock index can offer some diversification gains. However, other Chinese commodities may not be useful for portfolio diversification.     

Capturing the risk premium of commodity futures: The role of hedging pressure

We construct long–short factor mimicking portfolios that capture the hedging pressure risk premium of commodity futures. We consider single sorts based on the open interests of hedgers or speculators, as well as double sorts based on both positions. The long–short hedging pressure portfolios are priced cross-sectionally and present Sharpe ratios that systematically exceed those of long-only benchmarks. Further tests show that the hedging pressure risk premiums rise with the volatility of commodity futures markets and that the predictive power of hedging pressure over cross-sectional commodity futures returns is different from the previously documented forecasting power of past returns and the slope of the term structure.     

Factor pricing in commodity futures and the role of liquidity

This paper empirically investigates the pricing factors and their associated risk premiums of commodity futures. Existing pricing factors in equity and bond markets, including market premium and term structure, are tested in commodity futures markets. Hedging pressure in commodity futures markets and momentum effects is also considered. This study combines these factors to discuss their importance in explaining commodity future returns, while the literature has studied these factors separately. One of the important pricing factors in equity and bond markets is liquidity, but its role as a pricing factor in commodity futures markets has not yet been studied. To our knowledge, this research is the first to study liquidity as a pricing factor in commodity futures. The risk premiums of two momentum factors and speculators’ hedging pressure range from 2% to 3% per month and are greater than the risk premiums of roll yield (0.8%) and liquidity (0.5%). The result of a significant liquidity premium suggests that liquidity is priced in commodity futures.     

Permutation-weighted portfolios and the efficiency of commodity futures markets

Annals of Finance - We study the behavior of permutation-weighted portfolios, portfolios with weights that are proportional to a permutation of the current market weights. For markets with more...     

Markov models for commodity futures: theory and practice

The objective of this paper is to develop a generic, yet practical, framework for the construction of Markov models for commodity derivatives. We aim for sufficient richness to permit applications to a broad variety of commodity markets, including those that are characterized by seasonality and by spikes in the spot process. In the first, largely theoretical, part of the paper we derive a series of useful results concerning the low-dimensional Markov representation of the dynamics of an entire term structure of futures prices. Extending previous results in the literature, we cover jump-diffusive models with stochastic volatility as well as several classes of regime-switching models. To demonstrate the process of building models for a specific commodity market, the second part of the paper applies a selection of our theoretical results to the exercise of constructing and calibrating derivatives trading models for USD natural gas. Special attention is paid to the incorporation of empirical seasonality effects in futures prices, in implied volatilities and their ‘smile’, and in correlations between futures contracts of different maturities. European option pricing in our proposed gas model is closed form and of the same complexity as the Black–Scholes formula.     

Market efficiency and natural selection in a commodity futures market

While the literature usually justifies informational efficiencyin the context of rationality, this article shows informationalefficiency by applying the evolutionary idea of natural selection.In a dynamic futures market, speculators are assumed to merelyact upon their predetermined trading types (buyer or seller),their predetermined fractions of wealth allocated for speculation,and their inherent abilities to predict the spot price, reflectedin their distributions of prediction errors with respect tothe spot price. This article shows that the proportion of timethat the futures price equals the spot price converges to onewith probability 1.     

Trend-following trading strategies in commodity futures: A re-examination

This paper examines the performance of trend-following trading strategies in commodity futures markets using a monthly dataset spanning 48 years and 28 markets. We find that all parameterizations of the dual moving average crossover and channel strategies that we implement yield positive mean excess returns net of transactions costs in at least 22 of the 28 markets. When we pool our results across markets, we show that all of the trading rules earn hugely significant positive returns that prevail over most subperiods of the data as well. These results are robust with respect to the set of commodities the trading rules are implemented with, distributional assumptions, data-mining adjustments and transactions costs, and help resolve divergent evidence in the extant literature regarding the performance of momentum and pure trend-following strategies that is otherwise difficult to explain.     

Quantile connectedness between Chinese stock and commodity futures markets

In this study, we examine the static and dynamic connectedness between the conventional Chinese stock market and commodity futures (aluminum, gold, copper, steel rebar, natural rubber, and zinc). Our results show that both steel rebar and gold receive whereas zinc and copper transmit changes across all quantiles. However, spillover behavior of aluminum, natural rubber, and CSI 300 vary across different quantiles. Our results have implications for investors who are considering a mix of Chinese conventional stocks and commodity futures in their portfolios. Our findings also provide insights for investing under different market conditions by providing results for static as well as dynamic connectedness between CSI 300 and the commodities market.     

Predictability and diversification benefits of investing in commodity and currency futures

We re-examine diversification benefits of investing in commodities and currencies by considering a risk-averse investor with mean-variance preferences who exploits the possibility of predictable time variation in asset return means, variances, and covariances. We implement unconditional and conditional efficient portfolio strategies designed to exploit this predictability, together with more traditional and/or ad hoc ones yet hitherto relatively unexplored in this context (including the equally weighted, fixed weight, volatility timing, and reward-to-risk timing strategies). We find that, for all portfolio strategies, commodities and currencies do not improve the investment opportunity set of the investor with an existing portfolio of stocks, bonds and T-bills, and an investment horizon of one month. Our findings, which reverse the conclusions of previous studies that focus on static portfolio strategies, are robust across several performance metrics.     

Liquidity effects on price and return co-movements in commodity futures markets

Commodity price comovement is an important research area in finance, and previous studies have investigated the determinants of price comovement using low-frequency (monthly or quarterly) macroeconomic data. In comparison, our paper attempts to scrutinize the liquidity effect on commodity prices and return movements based on daily data. Our findings contribute to the literature in three ways. First, we find significant positively correlated price movements across different commodity markets on a daily basis, and such comovement is driven by the cross-sectional liquidity spillover effect. Second, we observe that a cointegration relationship between individual commodity prices and the global price index can be established only if the liquidity effect is controlled. Finally, instantaneous daily liquidity shocks (i.e., innovation) exert a negative impact on daily commodity returns. However, liquidity shocks do not have a significant impact on monthly returns. Our findings are robust and have significant implications for macroeconomic policymaking, such as managing inflation risk.