Strategic interaction between futures and spot markets

We study an oligopolistic industry where firms are able to sell in a futures market at infinitely many moments prior to the spot market. A kind of Folk-theorem is established: any outcome between perfect competition and Cournot can be sustained in equilibrium. We then find that the Cournot outcome can be sustained by a renegotiation-proof equilibrium. However, this is not true for the competitive outcome. Furthermore, only the monopolistic outcome is renegotiation-proof if firms can buy and sell in the futures market. These results suggest, contrary to existing literature, that the introduction of futures markets may have an anti-competitive effect.     

Volatility–volume causality across single stock spot–futures markets in India

This study examines the causal relationships between volatility and volume across spot and futures market for the 50 constituent stocks of the CNX NIFTY Index. Granger non-causality tests implemented using vector autoregression (VAR) and asymmetric VAR models indicate the presence of significant causal relations from both the spot and futures volume to both the spot and futures volatility. Bidirectional causal relationships between spot and futures volume were observed for almost all stocks but few stocks displayed a similar relationship between volatilities. The results highlight the importance of volume in absorbing information and its behaviour as the conduit of information.     

Index arbitrage and dynamics between REIT index futures and spot prices

This article contributes to the real estate literature by investigating the pricing relationship between REIT index futures and spot. Based on the cost-of-carry model, we first show that there exist three arbitrage regimes in Australia’s REIT spot-futures price dynamics. Further analysis indicates that the two thresholds, which separate the regimes, are largely consistent with the level dictated by transaction costs. We then estimate a threshold vector error correction model (TVECM). The results show that mean reversion of the mispricing error only takes place in the two outer regimes. Furthermore, we find evidence that REIT spot market is more informationally efficient than the futures market. Given its short history, it will take time for REIT index futures market to mature. Finally, we find that we can enhance hedging performance by accommodating the feature of threshold cointegration displayed by the data. As the futures-spot relationship differs across regimes, we can develop a hedging strategy by adjusting the hedge ratio based on arbitrage regimes. It leads to a greater variance reduction for the hedged portfolio than some conventional methods examined in the existing real estate literature.     

Price and volatility dynamics between securitized real estate spot and futures markets

This study is among the first to examine the price, volatility and covariance dynamics between securitized real estate spot and futures markets. It provides a distinctive and yet complementary perspective on the predictability of real estate spot return and spot volatility based on the information from the spot market alone. The results show that for the EPRA/NAREIT Europe index, the spot market tends to lead its futures market in the long run during the sample period, which can be attributed to a rather illiquid real estate futures market in sharp contrast with a voluminous spot market. Furthermore, we find the V-shaped asymmetric effect of the basis on the futures market volatility, which represents the primary channel of strong volatility transmission between securitized real estate spot and futures markets during the whole sample and the post-crisis period. This sheds light on the hedging effectiveness for the REIT index.     

Jumps and volatility dynamics in agricultural commodity spot prices

The spot commodities market exhibits both extreme volatility and price spikes, which lead to heavy-tailed distributions of price change and autocorrelation. This article uses various Lévy jump models to capture these features in a panel of agricultural commodities observed between January 1990 and February 2014. The results show that Levy jump models outperform the continuous Gaussian model. Our results prove that assuming a constant volatility or even a deterministic volatility and drift structure of agricultural commodity spot prices is not realistic and is less efficient than the stochastic assumption. The findings demonstrate an interesting correlation between volatility and jumps for a given commodity i, but no relationship between the volatility of commodity i and the probability of jumps of commodity j.     

Nonlinearities between oil spot and futures markets： Evidence from intraday data

This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is linear or not. The novelty of this work is based on intraday data from both markets. The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities. Moreover, non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality, a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.     

Are natural gas spot and futures prices predictable?

We answer two questions concerning natural gas spot and futures prices. The first is: Can natural gas futures prices predict natural gas spot prices? The second is: Are natural gas spot and futures prices weak form efficient or can they be predicted based on examination of historical data? To answer these questions, we use daily data for Henry Hub natural gas spot and futures prices. Our answer to the first question is that natural gas futures prices do not predict the magnitude of future natural gas spot prices any better than what would be predicted by a random walk model. This result has important implications for many financial analysts and policy institutions that have used commodity futures prices to predict movements in spot prices. The answer to the second question is that when we apply a unit root test that allows for heteroskedasticity and two structural breaks, natural gas spot and futures prices are predictable. We then simulate a contrarian trading strategy for spot and futures prices to show under what circumstances trading in spot and futures prices are also profitable. The results point to the need to accommodate heteroskedasticity when applying unit root tests to model energy spot and futures prices with high-frequency data, such as daily data.     

Intraday return and volatility relationships between the Ibex 35 spot and futures markets

This paper analyses the intraday lead-lag relationships between returns and volatilities in the Ibex 35 spot and futures markets. Using hourly data, we jointly analyze the interactions between markets, estimating a bivariate error correction model with GARCH perturbations which captures stochastically the presence of an intraday U-shaped curve for both spot and futures market volatility. Our findings show a bidirectional causal relationship between market volatilities, with a positive feedback. This two-way transmission of volatility is consistent with market prices evolving according to a long-run equilibrium relationship, and shocks affecting both markets in the same direction. Our empirical results also support a unidirectional cross interaction from futures to spot market returns. This pattern suggests that the futures market leads the spot market in order to incorporate the arrival of new information.     

An empirical investigation of causality between producers' price and consumers' price indices in Australia in frequency domain

The paper examines Granger-causality between the producers' and the consumers' price using Australian data within the frequency domain framework. For long run relation, the Johansen and Juselius (1990) maximum likelihood approach to cointegration was utilized. The test is also supplemented by the Breitung and Candelon (2006) and Lemmens et al. (2008) method. The quarterly data for the study covers 1969q3 to 2010q4. The findings suggest that consumers' price Granger-causes producers' price at an intermediate level of frequencies reflecting medium-run cycles, whereas producers' price does not Granger-cause consumers' price at any level of frequencies. Our study shows that consumers' price is a leading indicator of producers' price. Given that producers' price is used in making various macroeconomic indicators in real terms, the findings should help the Australian policymakers to gain control over the factors that affect consumers' price. The major contribution of the paper is to demonstrate unidirectional causality from consumers' price to the producers' price. Specifically, results show that consumers' price in Australian may have a significant predictive content in how the producers' price evolve. Furthermore, the application of the Breitung and Candelon (2006) and Lemmens et al. (2008) methodology in testing the Granger-causality in frequency domain is also relatively new.     

Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices

We propose a novel test to measure market efficiency while estimating the time-varying risk premiums of commodity futures, given that the prices are heteroscedastic. The risk premium is estimated using a state-space model with a Kalman filter modified for heteroscedasticity. Using 79 commodity futures traded on 16 exchanges during the period 2000–2014 and a Monte Carlo simulation, we demonstrate that the proposal produces robust results compared with conventional approaches. The global financial crisis has improved the efficiency and affected the trading volumes of commodity futures, but it has had no effect on the average or the volatility of risk premiums.     

A cointegration analysis of agricultural,energy and bio-fuel spot,and futures prices

This article features an analysis of the cointegration relationships among agricultural commodity, ethanol and Cushing crude oil spot, and future prices. The use of grains for the creation of bio-fuels has sparked fears that these demands are inflating food prices. We analyse approximately 10 years of daily spot and futures prices for corn, wheat, sugar ethanol, and oil prices from Datastream for the period 19 July 2006 to 2 July 2015. The analysis features Engle-Granger pairwise cointegration and partial cointegration. Pairs of series, that are cointegrated, are analysed using Markov-switching VECM and Impulse Response Analysis, which confirms that these markets have significant linkages that vary according to whether they are in low or high volatility regimes.     

Testing for causality between prices and money

The test for a causal relationship proposed byHaugh [1976] is considered in the context of the relationship between prices and money supply. The application of the test to 10 Latin American countries leads to the hypothesis of independence between the series being not rejected. Criticisms of the test are then discussed.     

The relationship between agricultural commodity prices,crude oil prices and US dollar exchange rates: a panel VAR approach and causality analysis

This study examines the relationship between crude oil prices, US dollar exchange rates and 30 selected international agricultural prices and five international fertilizer prices in a panel framework. The study uses panel VAR methods and Granger causality tests on panel data sets of agricultural commodity prices (as well as specific agricultural commodity sub-groups) and fertilizer prices with monthly observations of the period from June 1983 to June 2013. The empirical results of the present study indicate that crude oil prices as well as US dollar exchange rates affect international agricultural commodity and fertilizer prices. Furthermore, contrary to the findings of several studies in the literature, the present study supports bidirectional panel causality effects between crude oil prices and international agricultural prices as well as between US exchange rates and international agricultural prices.     

The dynamic causality between commodity prices,inflation and output in China: a bootstrap rolling window approach

In this article, we empirically study the time-varying bilateral causality between commodity prices, inflation and output in China. We first perform a series of parameter stability tests and find strong evidence of instability in the parameters estimated for Granger causality tests. We then use the bootstrap rolling window approach to test the causality and find that the causality from commodity prices to both inflation and output is time-varying in the entire sample period and asymmetric in different phases of the business cycle. We also find evidence of the causality from both inflation and output to commodity prices in certain sub-periods. Further discussion on the cost-price mechanism through which the economy fluctuates cyclically suggests that the dynamic causality between commodity prices and inflation contributes to understanding the nature of economic fluctuations and to forecasting economic crises. Overall, our results provide a new perspective to disentangle economic fluctuations.     

A common factor of stochastic volatilities between oil and commodity prices

This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.     

The heterogeneous dependence between global crude oil and Chinese commodity futures markets: evidence from quantile regression

This paper explores the dependence between global crude oil and Chinese commodity futures markets across different quantiles of the return distributions. Based on weekly data from 11 June 2004 to 7 July 2017, we address this issue by applying a quantile regression method. This technique provides a more detailed investigation of the dependence. Moreover, considering the structural breaks caused by market turmoil or financial crises, we divide the full period of every commodity sector market into sub-periods based on these break dates to further explore the dependence changes. The empirical results indicate that the dependence between global crude oil and Chinese commodity futures markets is different across quantiles in different commodity sectors. The dependence is significantly positive, except in markets with high expected returns. Additionally, the effects caused by structural breaks are distinctly heterogeneous across quantiles. The effect of the same break on the degree of dependence exhibits an increasing tendency as the quantile level increases, which suggests that markets with high expected returns are more susceptible to crises. Finally, we apply a prediction analysis to further verify the heterogeneity of the commodity sectors, which may be the cause of the heterogeneous dependence.     

Optimal use of futures markets when input and output prices are uncertain

The purpose of this paper is to extend the analysis of the use of futures markets by a competitive firm facing an uncertain market price for its output to the case where both input and output prices are uncertain.     

Are crude oil spot and futures prices cointegrated? Not always!

In previous studies, the cointegration relationships between crude oil spot and futures prices are confirmed based on Johansen (1988) test and vector error correction model (VECM). These conventional methods assume that the process of long-run equilibrium adjustment is linear. This paper revisits this topic employing nonlinear threshold VECM to take into account the nonlinear dynamics of equilibrium adjustment. Our results show that crude oil spot and futures prices are cointegrated only when the price differentials are larger than the threshold value. Moreover, we use a multi-frequency analysis based on low-pass filtering with different cut-off frequencies. The main findings indicate that the relationships between spot and futures prices are different between in the short-term and in the long-term. In the short-term, futures price plays the major role in the formation of long-run equilibrium (error correction mechanism). In the long-term, both spot and futures prices contribute to the dynamics of long-run equilibrium.     

Asymmetric causality using frequency domain and time-frequency domain (wavelet) approaches

Previous research that used asymmetric Granger causality tests relied upon data from the same time domain. In this paper we extend those tests theoretically to the frequency domain. We then apply these new tests to analyze causal link between nominal exchange rate and inflation in G6 and BRICS countries. For sensitivity analysis, we also apply time-frequency domain (wavelet) method in the context of asymmetric causality. Empirical results reveal that inflation causes the exchange rate in most of the countries in our sample. Our findings imply that anti-inflationary policies in these countries could stabilize the exchange rates and increase international confidence in attracting foreign investment which is important for sustained economic growth.