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.     

Computing the market price of volatility risk in the energy commodity markets

In this paper, we demonstrate the need for a negative market price of volatility risk to recover the difference between Black–Scholes [Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]/Black [Black, F., 1976. Studies of stock price volatility changes. In: Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, pp. 177–181] implied volatility and realized-term volatility. Initially, using quasi-Monte Carlo simulation, we demonstrate numerically that a negative market price of volatility risk is the key risk premium in explaining the disparity between risk-neutral and statistical volatility in both equity and commodity-energy markets. This is robust to multiple specifications that also incorporate jumps. Next, using futures and options data from natural gas, heating oil and crude oil contracts over a 10 year period, we estimate the volatility risk premium and demonstrate that the premium is negative and significant for all three commodities. Additionally, there appear distinct seasonality patterns for natural gas and heating oil, where winter/withdrawal months have higher volatility risk premiums. Computing such a negative market price of volatility risk highlights the importance of volatility risk in understanding priced volatility in these financial markets.     

Price limits in futures markets: effects on the price discovery process and volatility

Price limits are actively employed by many futures exchanges as a regulatory mechanism directed at reducing volatility and improving price discovery process. The aim of this paper is to investigate whether price limits achieve these goals without affecting market liquidity for a number of agricultural futures contracts. We employ models of changing volatility in order to show that price limits do not appear to significantly reduce market volatility. In addition, we find evidence confirming the hypothesis that price limits delay price discovery instead of facilitating it. Our results also suggest that the impact of price limits on volatility and price reversals, found in previous studies, are mainly due to the properties inherent to the futures returns, such as volatility clustering. Finally, although trading decreases significantly due to the price limits, traders do not seem to switch from the contracts affected by price limits to other maturities in order to minimize the impact of circuit breakers.     

Price discovery and volatility spillovers in index futures markets: Some evidence from Mexico

This paper investigates the hypotheses that the recently established Mexican stock index futures market effectively serves the price discovery function, and that the introduction of futures trading has provoked volatility in the underlying spot market. We test both hypotheses simultaneously with daily data from Mexico in the context of a modified EGARCH model that also incorporates possible cointegration between the futures and spot markets. The evidence supports both hypotheses, suggesting that the futures market in Mexico is a useful price discovery vehicle, although futures trading has also been a source of instability for the spot market. Several managerial implications are derived and discussed.     

Regime-switching volatility of six East Asian emerging markets

This paper investigates regime-switching behaviour in the return-generating processes of six East Asian emerging stock markets over the period from 1970 to 2004 and examines the specific characteristics of each regime by utilizing Markov-switching variance models. The results show very strong evidence of more than one regime in each of these stock markets. In addition, the conditional probabilities of each regime derived from the model provide mixed evidence regarding the impact of financial liberalization on return volatility.     

Stock volatility predictability in bull and bear markets

The recent literature on stock return predictability suggests that it varies substantially across economic states, being strongest during bad economic times. In line with this evidence, we document that stock volatility predictability is also state dependent. In particular, in this paper, we use a large data set of high-frequency data on individual stocks and a few popular time-series volatility models to comprehensively examine how volatility forecastability varies across bull and bear states of the stock market. We find that the volatility forecast horizon is substantially longer when the market is in a bear state than when it is in a bull state. In addition, over all but the shortest horizons, the volatility forecast accuracy is higher when the market is in a bear state. This difference increases as the forecast horizon lengthens. Our study concludes that stock volatility predictability is strongest during bad economic times, proxied by bear market states.     

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.     

Growing pains: The evolution of new stock index futures in emerging markets

Analyzing the first seven years of trading in Turkish stock index futures (BIST 30) and contrasting that to the progress of Korean (KOSPI 200) and Taiwanese (TAIEX) markets, we find that BIST 30 initially experiences a persistent mispricing and speculative trading similar to KOSPI 200 but it also experiences the largest increase in hedge effectiveness, becoming hedger-dominated similar to TAIEX. Most significantly, we demonstrate that spot market short-sell quote volume is a good measure of short-sale constraints and a significant determinant of mispricing in BIST 30. A methodological contribution of this paper is a four-equation multivariate VAR framework to analyze the volatility impact of futures.     

Contemporaneous intraday volume, option, and futures volatility transmissions across parallel markets

The primary objective of this article is to investigate volatility transmission across three parallel markets operating on the Sydney Futures Exchange (SFE), both within and out of sample. Half-hourly observations are sampled from transaction data for the share price index (SPI) futures, SPI futures options, and 90-day bank accepted bill (BAB) futures markets, and the analysis is carried out using the simultaneous volatility (SVL) system of equations as well as competing volatility models. The results confirm the poor ability of GARCH models to fit intraday data. This study also applies an artificial nesting procedure to evaluate the out-of-sample volatility forecasts. Implied volatility has very limited (if any) predictive power when evaluated in isolation, whereas the SVL model with implied volatility embedded provides incremental information relative to competing model forecasts.     

Price discovery in spot and futures markets: a reconsideration

We reconsider the issue of price discovery in spot and futures markets. We use a threshold error correction model to allow for arbitrage opportunities to have an impact on the return dynamics. We estimate the model using quote midpoints, and we modify the model to account for time-varying transaction costs. We find that (a) the futures market leads in the process of price discovery and (b) the presence of arbitrage opportunities has a strong impact on the dynamics of the price discovery process.     

The relation between implied and realised volatility in the Danish option and equity markets

We show that the conclusions to be drawn concerning the informational efficiency of illiquid options markets depend critically on whether one carefully recognises and appropriately deals with the econometrics of the errors‐in‐variables problem. This paper examines the information content of options on the Danish KFX share index. We consider the relation between the volatility implied in an option's price and the subsequently realised index return volatility. Since these options are traded infrequently and in low volumes, the errors‐in‐variables problem is potentially large. We address the problem directly using instrumental variables techniques. We find that when measurement errors are controlled for, call option prices even in this very illiquid market contain information about future realised volatility over and above the information contained in historical volatility.     

Currency futures, news releases, and uncertainty resolution

The effects of domestic macroeconomic news releases on futures on the British Pound (BP), Canadian Dollar (CD), Deutsche Mark (DM), Japanese Yen (JY), and Swiss Franc (SF) are examined. The results show that all five futures respond to the release of macroeconomic news, especially the first set of news releases issued at 7:30 a.m. (CST). Results of tests that identify the effects of individual announcements suggest that news in the Employment Report, the Trade Deficit, Industrial Production, and Capacity Utilization affects all five futures. Other announcements do not have such widespread effects. Volatility increases following the announcements persist for some time. Such increases are not uniform across the five instruments. For instance, following the 7:30-a.m. announcements, for the JY, BP, and SF, higher variance is observed for 30 min. However, for the DM and CD, the increase is 45 and 15 min, respectively.     

Reexamining intraday simultaneity in stock index futures markets

This note examines three empirical examples involving intraday dynamic relationships associated with stock index futures markets. Researchers often employ a vector autoregressive ( ) model to analyze such high frequency transactions data. While such a model can provide useful information regarding the nature of causal priority inherent in the data, it is not the proper model to investigate the structural relationships of interest, because it omits the contemporaneous interaction. On the other hand, a model specification which is altered to incorporate simultaneity may enable the data to reveal the structural relationships of interest.     

Financial liberalization and changes in the dynamic behaviour of emerging market volatility: Evidence from four Latin American equity markets

This paper examines whether the dynamic behaviour of stock market volatility for four Latin American stock markets (Argentina, Brazil, Chile and Mexico) and a mature stock market, that of the US, has changed during the last two decades. This period corresponds to years of significant financial and economic development in these emerging economies during which several financial crises have taken place. We use weekly data for the period January 1988 to July 2006 and we conduct our analysis in two parts. First, using the estimation of a Dynamic Conditional Correlation model we find that the short-term interdependencies between the Latin America stock markets and the developed stock market strengthened during the Asian, Latin American and Russian financial crises of 1997–1998. However, after the initial period of disturbance they eventually returned to almost their initial (relatively low) levels. Second, the estimation of a SWARCH-L model reveals the existence of more than one volatility regime and we detect a significant increased volatility during the period of crisis for all the markets under examination, although the capital flows liberalization process has only caused moderate shifts in volatility.     

Regulatory reform and market efficiency: The case of Indian agricultural commodity futures markets

We present the results of two efficiency measures that include intraday return predictability measure based on order imbalance and measures of several variance ratio tests on intraday subsamples of nine major Indian agricultural commodity futures (castor seed, cotton oil cake, rape mustard seed, soybean, refined soya oil, crude palm oil, jeera, chana, and turmeric) quoted in the National Commodity and Derivatives Exchange (NCDEX). We perform the efficiency measures on five subsamples with holding periods of 5, 10, 15, 30, and 60 min over two sample periods following the announcement of the merger between the Forward Market Commission (FMC) and Securities Exchange Board of India (SEBI). We compare results of tests of weak-form market efficiency of futures markets between two periods (pre-merger period and post-merger period). Our results confirm that Indian agricultural commodity futures markets continue to remain inefficient in the short-term during both pre-merger and post-merger periods. Based on these findings, it is likely that profitable trading strategies in the short intraday intervals will be available for traders and market participants during post-merger period. Thus, regulators must focus more on policy initiative so as to enhance market quality in order to address such inefficiencies in Indian commodity futures markets.     

The determination and international transmission of stock market volatility

This paper extends the literature on low-frequency analysis of the causes and transmission of stock market volatility. It uses end-monthly data on stock market returns, interest rates, exchange rates, inflation, and industrial production for five countries (Britain, France, Germany, Japan, and the US) from July 1973 to December 1994. Efficient portfolios of world, European, and Japanese/US equity are first constructed, the existence of multivariate cointegrating relationships between them is demonstrated, and the transmission of conditional volatility between them is described. The transmission of conditional volatility from world equity markets and national business cycle variables to national stock markets is then modeled. Among the main findings are: first, world equity market volatility is caused mostly by volatility in Japanese/US markets and transmitted to European markets, and second, changes in the volatility of inflation are associated with changes of the opposite sign in stock market volatility in all markets where a significant effect is found to exist. To the extent that the volatility of inflation is positively related to its level, this implies that low inflation tends to be associated with high stock market volatility.     

Are price limits on futures markets that cool? Evidence from the Brazilian Mercantile and Futures Exchange

This article investigates the impact of price limits on theBrazilian futures markets using high frequency data. The aimis to identify whether there is an ex ante cool-off or magneteffect. For that purpose, we examine a tick-by-tick data setthat includes all contracts on the São Paulo stock indexfutures traded on the Brazilian Mercantile and Futures Exchange(BM&F) from January 1997 to December 1999. The results indicatethat, altogether, there is a dominant cool-off effect in playand that the latter is much stronger for the floor rather thanceiling price. This explains why we observe more hits to theceiling rather than to the floor in our sample despite the factit covers one of the most turbulent periods for emerging markets.We then build a trading strategy that accounts for the cool-offeffect in the conditional mean so as to demonstrate that thelatter has not only statistical but also economic significance.The Sharpe ratio is indeed way superior to the buy-and-holdbenchmarks we consider.     

There's more to volatility than volume

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000 Ane, T and Geman, H. 2000. Order flow, transaction clock, and normality of asset returns. J. Finance, 55(5): 2259–2284. [Crossref], [Web of Science ®] , [Google Scholar]: J. Finance, 55, 2259–2284) and Gabaix et al. (2003 Gabaix, X, Gopikrishnan, P, Plerou, V and Stanley, H.E. 2003. A theory of power-law distributions in financial market fluctuations. Nature, 423: 267–270. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]: Nature, 423, 267–270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume.     

Information linkages between emission allowance and energy markets

We employ a rational expectations framework similar to that proposed by Fleming et al. (1998) to examine the source, and nature of, information linkages between the emission allowance and energy markets as gauged by the correlation of return volatilities. Estimating the model for bivariate pairings of securities suggests that market linkages arise from sensitivities to common information rather than from indirect spillovers, with emission allowances most strongly linked to the crude oil market.     

The effectiveness of incorporating higher moments in portfolio strategies: evidence from the Chinese commodity futures markets

This paper examines portfolio strategies that incorporate individual and systematic higher-order moments, within a stochastic optimization framework with uncertain mean and covariance. Using weekly, daily, and 30-minute interval data on Chinese commodity futures, we show that incorporating higher moments into portfolio strategies generally leads to better performance. The systematic fourth-order moment, among all systematic moments considered, can lead to the most robust, and a relatively large, improvement in investment performance, while the contribution of individual moments to the improved performance depends on the data horizon. We also find that adding higher moments brings superior performance in more cases for 30-minute-interval data than for other low-frequency data, suggesting that our strategy most likely performs best in 30-minute-rebalancing investments.