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.     

Limits to arbitrage and hedging: Evidence from commodity markets

We build an equilibrium model of commodity markets in which speculators are capital constrained, and commodity producers have hedging demands for commodity futures. Increases in producers' hedging demand or speculators' capital constraints increase hedging costs via price-pressure on futures. These in turn affect producers' equilibrium hedging and supply decision inducing a link between a financial friction in the futures market and the commodity spot prices. Consistent with the model, measures of producers' propensity to hedge forecasts futures returns and spot prices in oil and gas market data from 1979 to 2010. The component of the commodity futures risk premium associated with producer hedging demand rises when speculative activity reduces. We conclude that limits to financial arbitrage generate limits to hedging by producers, and affect equilibrium commodity supply and prices.     

Alternative models for hedging yield curve risk: An empirical comparison

We test alternative models of yield curve risk by hedging US Treasury bond portfolios through note/bond futures. We show that traditional implementations of models based on principal component analysis, duration vectors and key rate duration lead to high exposure to model errors and to sizable transaction costs, thus lowering the hedging quality. Also, this quality randomly varies from one model and hedging problem to the other. We show that accounting for the variance of modeling errors substantially reduces both hedging errors and transaction costs for all considered models. Additionally, it leads to much more stable weights in the hedging portfolios and – as a result – to more homogeneous hedging quality. On this basis, error-adjusted principal component analysis is found to systematically and significantly outperform alternative models.     

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.     

Swap variance hedging and efficiency: The role of high moments

In this article, we propose a new theoretical approach for developing hedging strategies based on swap variance (SwV). SwV is a generalized risk measure equivalent to a polynomial combination of all moments of a return distribution. Using the S&P 500 index and West Texas Intermediate (WTI) crude oil spot and futures price data, as well as simulations by varying the distribution of asset returns, we investigate the dynamic differences between hedge ratios and portfolio performances based on SwV (with high moments) and variance (without high moments). We find that, on average, the minimizing-SwV hedging suggests more short futures contracts than minimizing-variance hedging; however, when market conditions deteriorate, the minimizing-SwV hedging suggests fewer short positions in futures. The superior posthedge performances of the mean-SwV hedged portfolios over the mean-variance hedged portfolios in highly volatile or extremely calm markets confirm the efficiency of the mean-SwV hedging strategy.     

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.     

Investment shocks and the commodity basis spread

I identify a “slope” factor in the cross section of commodity futures returns: high-basis commodity futures have higher loadings on this factor than low-basis commodity futures. Combined with a level factor (an index of commodity futures), this slope factor explains most of the average excess returns of commodity futures portfolios sorted by basis. More importantly, I find that this factor is significantly correlated with investment shocks, which represent the technological progress in producing new capital. I investigate a competitive dynamic equilibrium model of commodity production to endogenize this correlation. The model reproduces the cross-sectional futures returns and many asset pricing tests.     

Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

The dynamic minimum variance hedge ratios (MVHRs) have been commonly estimated using the Bivariate GARCH model that overlooks the basis effect on the time-varying variance–covariance of spot and futures returns. This paper proposes an alternative specification of the BGARCH model in which the effect is incorporated for estimating MVHRs. Empirical investigation in commodity markets suggests that the basis effect is asymmetric, i.e., the positive basis has greater impact than the negative basis on the variance and covariance structure. Both in-sample and out-of-sample comparisons of the MVHR performance reveal that the model with the asymmetric effect provides greater risk reduction than the conventional models, illustrating importance of the asymmetric effect when modeling the joint dynamics of spot and futures returns and hence estimating hedging strategies.     

Hedging Pressure Effects in Futures Markets

We present a simple model implying that futures risk premia depend on both own-market and cross-market hedging pressures. Empirical evidence from 20 futures markets, divided into four groups (financial, agricultural, mineral, and currency) indicates that, after controlling for systematic risk, both the futures own hedging pressure and cross-hedging pressures from within the group significantly affect futures returns. These effects remain significant after controlling for a measure of price pressure. Finally, we show that hedging pressure also contains explanatory power for returns on the underlying asset, as predicted by the model.     

What does futures market interest tell us about the macroeconomy and asset prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.     

Basis‐Momentum

We introduce a return predictor related to the slope and curvature of the futures term structure: basis‐momentum. Basis‐momentum strongly outperforms benchmark characteristics in predicting commodity spot and term premiums in both the time series and the cross section. Exposure to basis‐momentum is priced among commodity‐sorted portfolios and individual commodities. We argue that basis‐momentum captures imbalances in the supply and demand of futures contracts that materialize when the market‐clearing ability of speculators and intermediaries is impaired, and that it represents compensation for priced risk. Our findings are inconsistent with alternative explanations based on storage, inventory, and hedging pressure.     

Regime switching correlation hedging

This paper investigates the hedging effectiveness of commodity futures when the correlations of spot and futures returns are subject to multi-state regime shifts. An independent switching dynamic conditional correlation GARCH (IS-DCC) which is free from the problems of path-dependency and recombining is applied to model multi-regime switching correlations. The results of hedging exercises indicate that state-dependent IS-DCC outperforms state-independent DCC GARCH and three-state IS-DCC exhibits superior hedging effectiveness, illustrating importance of modeling higher-state switching correlations for dynamic futures hedging.     

Business Cycles and Net Buying Pressure in the S&P 500 Futures Options

We analyse the cyclical behaviour and intraday pattern of net buying pressure in the S&P 500 futures options market. The results suggest that the net buying pressure of puts is counter‐cyclical and is more intense during contraction periods. The trading profits for selling put options during contraction periods thus far exceed those during expansion periods. Net buying pressure also exhibits an intraday pattern. Trading profits in the early trading sessions are higher than those for the rest of the day. In addition, we show that hourly‐basis hedging yields smaller profits than daily‐basis hedging, which suggests that the trading profits based on daily‐basis hedging may contain a risk premium associated with discretely rebalanced ‘risk‐free’ option portfolios.     

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.     

The predictability of aggregate returns on commodity futures

This paper provides evidence that aggregate returns on commodity futures (without the returns on collateral) are predictable, both in-sample and out-of-sample, by various lagged variables from the stock market, bond market, macroeconomics, and the commodity market. Out of the 32 candidate predictors we consider, we find that investor sentiment is the best in-sample predictor of short-horizon returns, whereas the level and slope of the yield curve have much in-sample predictive power for long-horizon returns. We find that it is possible to forecast aggregate returns on commodity futures out-of-sample through several combination forecasts (the out-of-sample return forecasting R² is up to 1.65% at the monthly frequency).     

The hedging effect of green bonds on carbon market risk

This paper explores effective hedging instruments for carbon market risk. Examining the relationship between the carbon futures returns and the returns of four major market indices, i.e., the VIX index, the commodity index, the energy index and the green bond index, we find that the connectedness between the carbon futures returns and the green bond index returns is the highest and this connectedness is extremely pronounced during the market's volatile period. Further, we develop and evaluate hedging strategies based on three dynamic hedge ratio models (DCC-APGARCH, DCC-T-GARCH, and DCC-GJR-GARCH models) and the constant hedge ratio model (OLS model). Empirical results show that among the four market indices the green bond index is the best hedge for carbon futures and performs well even in the crisis period. The paper also provides evidence that the dynamic hedge ratio models are superior to the OLS model in the volatile period as more sophisticated models can capture the dynamic correlation and volatility spillover between the carbon futures and market index returns.     

The Traditional Hedging Model Revisited with a Nonobservable Convenience Yield

This article examines the hedging of constrained commodity positions with futures contracts. We extend the study of Adler and Detemple (1988a, 1988b) to include a partial information framework where the convenience yield is not observable. As a consequence, futures prices depend on investor's beliefs regarding the value of the convenience yield, and every component of the hedge is impacted by these beliefs. We achieve a decomposition of the demand that clarifies the impact on the optimal hedge of the beliefs, the spot price and the risk‐free rate as well as the hedging horizon.     

Momentum strategies based on reward–risk stock selection criteria

In this paper, we analyze momentum strategies that are based on reward–risk stock selection criteria in contrast to ordinary momentum strategies based on a cumulative return criterion. Reward–risk stock selection criteria include the standard Sharpe ratio with variance as a risk measure, and alternative reward–risk ratios with the expected shortfall as a risk measure. We investigate momentum strategies using 517 stocks in the S&P 500 universe in the period 1996–2003. Although the cumulative return criterion provides the highest average monthly momentum profits of 1.3% compared to the monthly profit of 0.86% for the best alternative criterion, the alternative ratios provide better risk-adjusted returns measured on an independent risk-adjusted performance measure. We also provide evidence on unique distributional properties of extreme momentum portfolios analyzed within the framework of general non-normal stable Paretian distributions. Specifically, for every stock selection criterion, loser portfolios have the lowest tail index and tail index of winner portfolios is lower than that of middle deciles. The lower tail index is associated with a lower mean strategy. The lowest tail index is obtained for the cumulative return strategy. Given our data-set, these findings indicate that the cumulative return strategy obtains higher profits with the acceptance of higher tail risk, while strategies based on reward–risk criteria obtain better risk-adjusted performance with the acceptance of the lower tail risk.     

股指期货与股指期权套期保值组合的Delta中性动态模拟——基于沪深300股指期货仿真交易的分析

沪深300股指期货的推出,在为市场提供套保工具和流动性的同时,也带来新的风险。本文运用同一指数的股指期权与股指期货组成多种动态套期保值组合,分析股指期货的风险对冲策略。结果表明所构造的组合都能为股指期货提供有效的套期保值;不论多头股指期货还是空头股指期货,保护性策略的风险控制能力更强。     

Hedging long-term exposures with multiple short-term futures contracts

This article analyzes the problem facing an agent who has along-term commodity supply commitment and who wishes to hedgethat commitment using short-maturity commodity futures contracts.As time evolves, the agent has to roll the hedge as old futurescontracts mature and new futures contracts are listed. Thisgives rise to hedge errors. The optimal hedging strategy ischaracterized in a world where contracts of several differentmaturities coexist. The strategy is independent both of theagent's risk aversion and, under certain conditions, of beliefsabout expected returns from holding futures contracts. The methodologyis compared with approaches based on dynamic models of the termstructure. It is tested on data from the oil futures market.