An Anatomy of Commodity Futures Risk Premia

We identify two types of risk premia in commodity futures returns: spot premia related to the risk in the underlying commodity, and term premia related to changes in the basis. Sorting on forecasting variables such as the futures basis, return momentum, volatility, inflation, hedging pressure, and liquidity results in sizable spot premia between 5% and 14% per annum and term premia between 1% and 3% per annum. We show that a single factor, the high‐minus‐low portfolio from basis sorts, explains the cross‐section of spot premia. Two additional basis factors are needed to explain the term premia.     

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.     

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.     

A new strategy using term-structure dynamics of commodity futures

The term structure of commodity futures is important information for traders and investors. Traditional term-structure strategies are static; they tend to use the slope of term structure at a given moment. Instead, our trading strategy uses the change of term structure and generates statistically significant return. It also produces significant abnormal return in excess of the traditional two factors, i.e. the returns from static-slope strategy and daily momentum. Thus, its return includes orthogonal information or excess return that standard static-slope and momentum strategies cannot explain. This suggests a novel risk factor in the asset class of commodity futures or robust trading opportunities.     

中国大宗商品期货市场定价机制研究

大宗商品期货市场是我国资本市场的重要组成部分,其定价有效性关系到投资者套期保值和价格发现等功能的实现。本文对国际前沿研究中常用的定价因子进行全面系统梳理,并对这些因子对我国商品期货合约收益率的解释和预测能力进行检验。在此基础上,本文构建了适用于我国大宗商品期货市场的包含市场、基差以及基差动量的三因子定价模型。进一步研究表明,基于大宗商品存储理论和现货存货数据构建的投资组合收益率可以被本文三因子模型有效解释,验证了经典的存储理论在我国的适用性。此外,本文对基差与基差动量两个重要因子的经济学意义进行了阐释。本文研究为进一步厘清大宗商品期货市场定价机制提供了一定参考。     

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.     

Is idiosyncratic volatility priced in commodity futures markets?

This article investigates the relationship between expected returns and past idiosyncratic volatility in commodity futures markets. Measuring the idiosyncratic volatility of 27 commodity futures contracts with traditional pricing models that fail to account for backwardation and contango leads to the puzzling finding that idiosyncratic volatility is significantly negatively priced cross-sectionally. However, idiosyncratic volatility is not priced when the phases of backwardation and contango are suitably factored in the pricing model. A time-series portfolio analysis similarly suggests that failing to recognize the fundamental risk associated with the inexorable phases of backwardation and contango leads to overstated profitability of the idiosyncratic volatility mimicking portfolios.     

Is idiosyncratic asymmetry priced in commodity futures?

In this article, we use a recently introduced asymmetry measure, IE, to measure the idiosyncratic asymmetry of commodity futures returns and find that idiosyncratic asymmetry negatively and significantly predicts commodity futures returns cross sectionally. Furthermore, we find that a long–short trading strategy based on idiosyncratic asymmetry generates significant abnormal returns, which cannot be explained by traditional risk factors in commodity futures and persists up to 12 months. Moreover, idiosyncratic asymmetry appears to be a priced factor in commodity futures with significant risk premium. Finally, we confirm that IE is better at capturing the pricing effect of idiosyncratic asymmetry than the traditional skewness measure.     

Default Premiums in Commodity Markets: Theory and Evidence

We model the effect of nonperformance risk on forward and futures pricing and look for evidence of nonperformance risk in precious metals futures prices from the “Hunt Brothers”episode. Changes in default premiums are measured and related to the sequence of events in the metals markets during this period. Results suggest first that ex ante costs of nonperformance can be a significant, priced factor in commodity markets and second that the arrival of new information is often associated with changes in these costs. The evidence has implications for both theoretical and empirical research on commodity markets.     

Trend following,risk parity and momentum in commodity futures

We show that combining momentum and trend following strategies for individual commodity futures can lead to portfolios which offer attractive risk adjusted returns which are superior to simple momentum strategies; when we expose these returns to a wide array of sources of systematic risk we find that robust alpha survives. Experimenting with risk parity portfolio weightings has limited impact on our results though in particular is beneficial to long–short strategies; the marginal impact of applying trend following methods far outweighs momentum and risk parity adjustments in terms of risk-adjusted returns and limiting downside risk. Overall this leads to an attractive strategy for investing in commodity futures and emphasises the importance of trend following as an investment strategy in the commodity futures context.     

Asymmetry,tail risk and time series momentum

In this paper, we investigate how to improve the time series momentum strategy by using partial moments. We find that reversals of time series momentum can be partly predicted by tail-distributed upper and lower partial moments derived from daily returns of commodity futures. Based on such information, we propose rule-based approaches to improve the trading signals suggested by the time series momentum strategy. The empirical results based on Chinese commodity futures document statistically significant improvements of the Sharpe ratio in the out-of-sample period. These improvements are robust to different look-back windows.     

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.     

Does Index Speculation Impact Commodity Prices? An Intraday Analysis

Using intraday data, we find unidirectional causality from commodity index‐linked futures to nonindex‐linked commodity futures for up to one hour which disappears when using daily data. Also, the economic significance of index‐linked to nonindex commodity transmission declines to zero within about an hour. Finally, we find that the magnitude of index‐linked to nonindex return transmission is positively related to the amount of speculation, both long and short, in S&P GSCI commodity index futures. We conclude that speculative pressures exerted by commodity index futures can impact nonindex commodities, mainly through the activity of uninformed, positive feedback traders.     

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.     

Do Low‐Priced Stocks Drive Long‐Term Contrarian Performance on the London Stock Exchange?

We investigate whether low‐priced stocks drive long‐term contrarian performance on the U.K. market. We find that contrarian performance at low, middle, and high price levels is positive. On the Fama‐French risk adjusted basis, we find both low‐priced and middle‐priced losers have significantly positive returns. When we adjust returns by market and liquidity risk, only middle‐priced losers maintain their positive returns. Our results reveal that low‐priced stocks are not fully responsible for contrarian performance. Our empirical evidence is generally consistent with the overreaction hypothesis and behavioral models of value investing.     

A Nonlinear Factor Analysis of S&P 500 Index Option Returns

Growing evidence suggests that extraordinary average returns may be obtained by trading equity index options, and that at least part of this abnormal performance is attributable to volatility and jump risk premia. This paper asks whether such priced risk factors are alone sufficient to explain these average returns. To provide an answer in as general as possible a setting, I estimate a flexible class of nonlinear models using all S&P 500 Index futures options traded between 1986 and 2000. The results show that priced factors contribute to these expected returns but are insufficient to explain their magnitudes, particularly for short‐term out‐of‐the‐money puts.     

Strategic commodity allocation

This article extends the study of the financialization of commodities (Rouwenhorst and Tang [Annu. Rev. Financ. Econ., 2012, 4, 447–467]) by considering an investment in the term structure of commodity futures prices. Specifically, we analyse the benefits of adding a distant commodity futures contract and/or a spot commodity (near month futures contract) to a portfolio of bonds and stocks in a setting similar to Brennan and Schwartz [The use of treasury bill futures in strategic asset allocation programs. In Worldwide Asset and Liability Modeling, edited by W.T. Ziemba and J.M. Mulvey, pp. 205–230, 1998 (Cambridge University Press: Cambridge)]. Our analysis employs an empirical study that covers the post financial crisis period. We show that the spot commodity considerably improves the value of the portfolio. However, an investment in the whole term structure of futures contracts is optimally achieved through high opposite positions in the spot commodity and distant futures contracts. We find that these extreme calendar spreads can result in an inappropriate investment.     

A Model of Financialization of Commodities

We analyze how institutional investors entering commodity futures markets, referred to as the financialization of commodities, affect commodity prices. Institutional investors care about their performance relative to a commodity index. We find that all commodity futures prices, volatilities, and correlations go up with financialization, but more so for index futures than for nonindex futures. The equity‐commodity correlations also increase. We demonstrate how financial markets transmit shocks not only to futures prices but also to commodity spot prices and inventories. Spot prices go up with financialization, and shocks to any index commodity spill over to all storable commodity prices.     

Liquidity and the Law of One Price: The Case of the Futures-Cash Basis

Deviations from no‐arbitrage relations should be related to market liquidity, because liquidity facilitates arbitrage. At the same time, a wide futures‐cash basis may trigger arbitrage trades and, in turn, affect liquidity. We test these ideas by studying the dynamic relation between stock market liquidity and the index futures basis. There is evidence of two‐way Granger causality between the short‐term absolute basis and liquidity, and liquidity Granger‐causes longer‐term absolute bases. Shocks to the absolute basis predict future stock market liquidity. The evidence suggests that liquidity enhances the efficiency of the futures‐cash pricing system.     

Commodity price modelling that matches current observables: a new approach

We develop a stochastic model of the spot commodity price and the spot convenience yield such that the model matches the current term structure of forward and futures prices, the current term structure of forward and futures volatilities, and the inter-temporal pattern of the volatility of the forward and futures prices. We let the underlying commodity price be a geometric Brownian motion and we let the spot convenience yield have a mean-reverting structure. The flexibility of the model, which makes it possible to simultaneously achieve all these goals, comes from allowing the volatility of the spot commodity price, the speed of mean-reversion parameter, the mean-reversion parameter, and the diffusion parameter of the spot convenience yield all to be time-varying deterministic functions.