Dynamic spillover effects across petroleum spot and futures volatilities,trading volume and open interest

This paper examines the existence of dynamic spillover effects across petroleum based commodities and among spot-futures volatilities, trading volume and open interest. Realized volatilities of spot-futures markets are used as inputs to estimate a VAR model following Diebold and Yilmaz (2014, 2015) and distinguish dynamic spillovers in total and net effects. Results reveal the existence of large and time-varying spillovers among the spot-futures volatilities and across petroleum-based commodities when examined pairwise. In addition, speculative pressures, as reflected by futures trading volume, and hedging pressures, as reflected by open interest, are shown to transmit large and persistent spillovers to the spot and futures volatilities of crude oil and heating oil-gasoline markets, respectively.     

Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments

This study examines how speculative and hedging sentiments influence the returns and volatilities of energy futures markets. We construct speculative and hedging sentiment indices based on the weekly data of fund and commercial positions of four energy futures: crude oil, heating oil, gasoline, and natural gas, traded on the New York Mercantile Exchange (NYMEX) from 15 January 2013 to 5 February 2019. Our study demonstrates that speculative sentiment generates greater market fluctuations in the energy futures markets than hedging sentiment; and, further, speculative sentiment stimulates a reversal effect on the returns of crude oil futures. Moreover, speculative sentiment exerts positive systemic risk compensation on the four futures' returns, whereas hedging sentiment alleviates volatilities in the energy futures markets. Most notably, distinguishing it from the leverage effect in stock markets, the speculative sentiment in the energy futures markets is influenced more by good than by bad news; while hedging sentiment exhibits emotional neutrality, as opposed to its impact on stock markets as reported in the literature. Additionally, the positive hedging sentiment in crude oil futures demonstrates significant systemic risk compensation, whereas the three other futures do not have an influence, confirming the prevalence of speculation in hedging transactions in crude oil futures. Our further analysis shows cross-market volatility spillover effects, among which speculative sentiment inherent in crude oil futures causes volatility spillovers to the three other futures, while hedging sentiment has no such effect. Our study has implications for overseeing international energy futures markets, providing regulators with evidence that will facilitate the development of effective strategies to strengthen market supervision.     

Soft commodities and the global financial crisis: Implications for the economy,resources and institutions

Over the past decade, soft commodities have been subjected to increasing speculative price fluctuations. Following the 2008 financial crisis, most studies have highlighted causal relationships between price volatility, derivative and future markets for underlying financial assets as well as agricultural and mineral commodities. This article investigates the multifaceted effects of unrestrained financialization of the resources and goods markets and its implications for agricultural markets and soft commodities for purposes other than direct human consumption. We place a particular emphasis on the process of commodification of food and non-food crops and their use as green source of liquid fuels (i.e. soy, sugar cane, palm oil, jatropha, and canola). It is argued that speculation in financial markets has led to spillover effects across commodity and resource markets. More importantly, speculation and price volatility in the commodity markets has had a direct bearing on the resource markets and organization and appropriation of common-pool resources. The article sheds further light on the causal relationship between derivative markets, hedging techniques, financial yields and price volatility and spillover effects in the market for food and soft commodities.     

Will tighter futures price limits decrease hedge effectiveness?

The events triggered by the Global Financial Crisis (GFC) have led to calls for the regulation of financial markets. Given that regulation may involve opportunity costs, this paper examines whether tighter futures price limits can reduce the effectiveness of a futures hedge. We propose a new model that uncovers the underlying spot-futures dynamics when futures prices are subject to limits. We use the model to determine the maximum number of limit days that can occur before minimum variance hedging outcomes are adversely affected. Application of this model to the US soybean and corn markets reveals that existing limits do not reduce hedge effectiveness. If the frequency of limit days increases from current levels of 1% to approximately 3–4%, conventional hedging approaches will experience economically and statistically significant increases in portfolio variance. These results are important for hedgers, clearing houses and regulators in light of the recent calls for derivatives regulation.     

Hedging effectiveness of the Athens stock index futures contracts

This paper examines the hedging effectiveness of the FTSE/ATHEX-20 and FTSE/ATHEX Mid-40 stock index futures contracts in the relatively new and fairly unresearched futures market of Greece. Both in-sample and out-of-sample hedging performances using weekly and daily data are examined, considering both constant and time-varying hedge ratios. Results indicate that time-varying hedging strategies provide incremental risk-reduction benefits in-sample, but under-perform simple constant hedging strategies out-of-sample. Moreover, futures contracts serve effectively their risk management role and compare favourably with results in other international stock index futures markets. Estimation of investor utility functions and corresponding optimal utility maximising hedge ratios yields similar results, in terms of model selection. For the FTSE/ATHEX Mid-40 contracts we identify the existence of speculative components, which lead to utility-maximising hedge ratios, that are different to the minimum variance hedge ratio solutions.     

Selective hedging strategies for crude oil futures based on market state expectations

This paper studies the ex-ante selective hedging strategies of crude oil futures contracts based on market state expectations and compares the hedging performances to the traditional minimum variance routine hedging strategies. The main advantage of the proposed method is that it achieves a trade-off between return and risk, rather than hedges risk at all costs. Specifically, we first use a multi-input Hidden Markov Model(HMM) to identify the market state, assess the market’s herding impact, and then integrate the findings of identification and measurement to forecast the price trend. We offer an adjustment criterion for the hedge ratios driven by GARCH²-type models based on the anticipated market state. We conducted an empirical analysis to examine the hedging effect of WTI and Brent crude oil futures, the results indicate that the proposed state-dependent hedging strategies are superior to the traditional model-driven hedging strategies concerning the hedged portfolio based on four criteria. The robustness check reveals that the proposed hedging strategies still outperform in different market situation. The findings can help traders in the crude oil markets, and the methodology can be applied to other energy markets.     

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.     

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.     

Long term spread option valuation and hedging

This paper investigates the valuation and hedging of spread options on two commodity prices which in the long run are in dynamic equilibrium (i.e., cointegrated). The spread exhibits properties different from its two underlying commodity prices and should therefore be modelled directly. This approach offers significant advantages relative to the traditional two price methods since the correlation between two asset returns is notoriously hard to model. In this paper, we propose a two factor model for the spot spread and develop pricing and hedging formulae for options on spot and futures spreads. Two examples of spreads in energy markets – the crack spread between heating oil and WTI crude oil and the location spread between Brent blend and WTI crude oil – are analyzed to illustrate the results.     

Quantifying the speculative component in the real price of oil: The role of global oil inventories

One of the central questions of policy interest in recent years has been how many dollars of the inflation-adjusted price of oil must be attributed to speculative demand for oil stocks at each point in time. We develop statistical tools that allow us to address this question, and we use these tools to explore how the use of two alternative proxies for global crude oil inventories affects the empirical evidence for speculation. Notwithstanding some differences, overall these inventory proxies yield similar results. While there is evidence of speculative demand raising the price in mid-2008 by between 5 and 14 dollars, depending on the inventory specification, there is no evidence of speculative demand pressures between early 2003 and early 2008. As a result, current policy efforts aimed at tightening the regulation of oil derivatives markets cannot be expected to lower the real price of oil in the physical market. We also provide evidence that the Libyan crisis in 2011 shifted expectations in oil markets, resulting in a price increase of between 3 and 13 dollars, depending on the inventory specification. With regard to tensions with Iran in 2012, the implied price premium ranges from 0 to 9 dollars.     

A Likelihood Ratio Test of Price Volatilities: Comparing Stock Index Spot and Futures

This paper uses three methods to estimate the price volatility of two stock market indexes and their corresponding futures contracts. The classic variance measure of volatility is supplemented with two newer measures, derived from the Garman-Klass and Ball-Torous estimators. A likelihood ratio test is used to compare the classic variance measure of price volatilities of two stock market indexes and their corresponding futures contracts during the bull market of the 1980s. The stock market volatilities of the Standard & Poor's 500 (S&P 500) and New York Stock Exchange (NYSE) indexes were found to be significantly lower than their respective futures price volatilities. Since information may flow faster in the futures markets than in the corresponding stock market, our results support Ross's information-volatility hypothesis. It was also noted that the NYSE spot volatility was lower than the S&P 500 spot volatility. If the rate of information flow and firm size are positively related, then the lower NYSE spot volatility is explained by the size effect. The futures price volatilities for the two indexes were insignificantly different from each other. With stock index spot-futures price correlations approaching unity, one implication of our results for index futures activity is that smaller positions in futures contracts may suffice to achieve hedging or arbitrage goals.     

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.     

Trades in commodities,financial assets,and currencies: A triangle of arbitrage,hedging and speculative designs

This work brings three markets — (i) commodities (e.g., steel iron ores, electronic parts, oil), (ii) financial assets (such as various stocks, bonds, notes), and (iii) different currencies (like U.S. dollar, British pound, euro, yen and so on) and examines the scope of triple operations of arbitrage, hedging, and speculation. Trading of cross-listed cross-currency assets with arbitrage and hedging is already recorded and analyzed. Here one more dimension — cross-country trades in commodities are added, and speculation is juxtaposed too within one framework.     

Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?

The Shanghai International Energy Exchange (INE) facilitates both local and international investment in Chinese petrochemical-related stocks through local crude oil futures. This study investigates whether the Chinese emerging market can better aid investors' risk hedging and asset allocation compared to two major international developed markets–the Brent and West Texas Intermediate (WTI) crude oil futures markets—and examines the pairwise risk hedging effects and multi-asset allocation performance of INE and petrochemical-related stocks. The results show that INE has higher hedge effectiveness than Brent and WTI under pairwise hedging. Further, in multi-asset allocation, the portfolios containing INE outperform other portfolios. Overall, INE results in a better diversification effect and volatility reduction than the use of WTI crude oil futures to construct multi-asset allocation with Chinese petrochemical-related stocks. However, INE performance is inferior to Brent's in terms of constructing portfolios with oil or energy stocks. Finally, our results are robust to the five factors proposed by Fama and French (2015) in asset pricing.     

Consumption and Hedging in Oil‐Importing Developing Countries

We study the consumption and hedging strategy of an oil‐importing developing country that faces multiple crude oil shocks. In our model, developing countries have two particular characteristics: their economies are mainly driven by natural resources and their technologies are less efficient in energy usage. The natural resource exports can be correlated with the crude oil shocks. The country can hedge against the crude oil uncertainty by taking long/short positions in existing crude oil futures contracts. We find that both inefficiencies in energy usage and shocks to the crude oil price lower the productivity of capital. This generates a negative income effect and a positive substitution effect, because today’s consumption is relatively cheaper than tomorrow’s consumption. Optimal consumption of the country depends on the magnitudes of these effects and on its risk‐aversion degree. Shocks to other crude oil factors, such as the convenience yield, are also studied. We find that the persistence of the shocks magnifies the income and substitution effects on consumption, thus also affecting the hedging strategy of the country. The demand for futures contracts is decomposed in a myopic demand, a pure hedging term and productive hedging demands. These hedging demands arise to hedge against changes in the productivity of capital due to changes in crude oil spot prices. We calibrate the model for Chile and study to what extent the country’s copper exports can be used to hedge the crude oil risk.     

Multiperiod hedging in the presence of stochastic volatility

In this paper, we characterize the multiperiod minimum-risk hedge strategy within the stochastic volatility (SV) framework and compare it to other hedge strategies on the basis of hedging performance. Using crude oil markets as an example, we demonstrate that the SV model is appropriate in depicting price behaviour. However, ex ante and ex post comparisons indicate that the SV strategy is inferior to conventional hedging strategies. There is also evidence that the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) strategy may be better than the SV strategy, at least in terms of variance reduction.     

Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges

Some studies have revealed the hedging ability of Bitcoin against stock markets, but the knowledge of how it compares with other hedges is in its infancy. This paper presents the first study on time-frequency domain connectedness and hedging among five hedges (Bitcoin, crude oil, commodities, gold and the U.S. dollar (USD) index) and four stock indices (developed markets ex U.S., emerging markets ex China, U.S. and China). We find that the connectedness between hedges and stock markets varies by time across time horizons. Specifically, the connectedness between Bitcoin and stock indices is the smallest among all hedges, especially for the short horizon. Gold and USD are isolated from other markets at longer horizons. The hedging ratio, optimal portfolio weights and hedging effectiveness also vary across investment horizons. For short-term investment, gold has better hedging effectiveness, especially for emerging stock markets and the U.S. stock market. For median- and long-term investment, USD has better performance, especially for developed markets ex U.S. and emerging stock markets. Additionally, although Bitcoin has good hedging properties, it has high volatility compared with other hedging assets. In other words, if Bitcoin is included in a portfolio, investors should pay attention to its wide variation. These empirical findings highlight the important role that gold and USD play in hedging against global stock markets.     

Volatility spillovers between oil prices and the stock market under structural breaks

This paper employs univariate and bivariate GARCH models to examine the volatility of oil prices and US stock market prices incorporating structural breaks using daily data from July 1, 1996 to June 30, 2013. We endogenously detect structural breaks using an iterated algorithm and incorporate this information in GARCH models to correctly estimate the volatility dynamics. We find no volatility spillover between oil prices and US stock market when structural breaks in variance are ignored in the model. However, after accounting for structural breaks in the model, we find strong volatility spillover between the two markets. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our empirical results which underscores the serious consequences of ignoring these structural breaks. Our findings are consistent with the notion of cross-market hedging and sharing of common information by financial market participants in these markets.     

Monetary policy and speculative spillovers in financial markets

This paper examines the role of monetary policy (MP) as a driver of connectedness patterns in speculative activities in financial markets. Examining measures of speculation in four major markets including gold, equities, Treasury bonds and crude oil, we show that speculative activities can spill over across markets with the stock market generally serving as the main transmitter of speculative shocks. While unconventional MP is associated with greater connectedness of speculative activities in financial markets, we also find that unconventional (conventional) MP drives gold (financial assets) to serve as a net transmitter of speculative shocks to the other markets. The findings establish an important link between the monetary policy signals and trading behavior in financial markets with significant policy implications.     

Statistical properties of post-sample hedging effectiveness

This paper examines the mean and the variance of post-sample hedging effectiveness. It is shown that, the hedging effectiveness measure adopted in the current literature is a biased estimator of the true hedging effectiveness. Moreover, it underestimates the true hedging effectiveness. Empirical results base upon twenty-four futures markets for the error correction hedge ratio, however, suggest the bias is negligible. On the other hand, in some markets, the variance of the hedging effectiveness is too large for the estimate to be reliable.