Economic linkages across commodity futures: Hedging and trading implications

We investigate cross-market trading dynamics in futures contracts written on seemingly unrelated commodities that are consumed by a common industry. On the Tokyo Commodity Exchange, we find such evidence in natural rubber (NR), palladium (PA) and gasoline (GA) futures markets. The automobile industry is responsible for more than 50% of global demand for each of these commodities. VAR estimation reveals short-run cross-market interaction between NR and GA, and from NR to PA. Cross-market influence exerted by PA is felt in longer dynamics, with PA volatility (volume) affecting NR (GA) volume (volatility). Our findings are robust to lag-specification, volatility measure, and consistent with full BEKK-GARCH estimation results. Further analysis, which benchmarks against silver futures market, TOCOM index and TOPIX transportation index, confirms that our results are driven by a common industry exposure, and not a commodity market factor. A simple trading rule that incorporates short-run GA and long-run PA dynamics to predict NR return yields positive economic profit. Our study offers new insights into how commodity and equity markets relate at an industry level, and implications for multi-commodity hedging.     

Information transmission in informationally linked markets: Evidence from US and Chinese commodity futures markets

This paper investigates information transmission and price discovery in informationally linked markets within the multivariate generalized autoregressive conditional heteroskedasticity and information share frameworks. Based on both synchronous and non-synchronous trading information from Chinese futures/spot markets, the New York Mercantile Exchange (NYMEX), Chicago Board of Trade (CBOT), and CME Globex futures markets for copper and soybeans, we show that there is a bidirectional relationship in terms of price and volatility spillovers between US and Chinese markets, with a stronger effect from US to Chinese markets than the other way around. Additionally, the NYMEX and CBOT play a more important role than the CME Globex in the flow of information from US to Chinese markets. Moreover, we find that Chinese copper market adjusts more quickly than the NYMEX copper market to correct the disparity between both markets. However, the converse is true in the case of soybeans. Finally, our results highlight the remarkable role of Chinese futures markets in the price formation process, though NYMEX and CBOT futures markets are the main driving force in price discovery.     

A Model of Returns and Trading in Futures Markets

This paper develops an equilibrium model of a competitive futures market in which investors trade to hedge positions and to speculate on their private information. Equilibrium return and trading patterns are examined. (1) In markets where the information asymmetry among investors is small, the return volatility of a futures contract decreases with time-to-maturity (i.e., the Samuelson effect holds). (2) However, in markets where the information asymmetry among investors is large, the Samuelson effect need not hold. (3) Additionally, the model generates rich time-to-maturity patterns in open interest and spot price volatility that are consistent with empirical findings.     

International transmission of information: evidence from the Euroyen and Eurodollar futures markets

This paper examines the information transmission between Japan and the US by using the Tokyo Euroyen and Chicago Eurodollar futures. These two interest rate futures markets provide a better understanding of international information transmission than stock markets, which have been shown to exhibit nonsynchronous trading and market segmentation. The results show that traders in Tokyo (Chicago) use information that is revealed overnight in Chicago (Tokyo). The bivariate EGARCH-t model provides no evidence of volatility spillovers in either direction, suggesting that the opening price rapidly reflects foreign information. The overall results support the hypothesis that the domestic market efficiently adjusts to foreign news. The results are also broadly consistent with the covered interest arbitrage effects.     

Volatility linkage among currency futures markets during US trading and non-trading periods

This paper examines the volatility transmission across different currency markets during trading and non-trading periods. Using vector autoregressive analysis (VAR), we find similar patterns between information flows during trading and non-trading hours of the US currency futures exchange. The results indicate that trading-hour information and non-trading-hour information have similar effects on currency prices and that the markets do not differentiate information based upon the timing of its release. Our study observes that currencies exhibit different levels of global linkage and appear to play different informational roles in the currency market. Additionally, this study observes a trend toward increased integration among the currency futures markets.     

Stock market closure and intraday stock index futures market volatility: “contagion”, bid–ask bias or both?

Chang et al. [Journal of Business 68 (1) (1995) 61] examine the impact of the closure of the New York Stock Exchange (NYSE) on S&P500 stock index futures traded on the Chicago Mercantile Exchange. They document a decline in futures market volatility immediately after the close of the NYSE, and an increase 15 minutes later when the futures market closes. They attribute this to contagion–i.e. a decline in information transfer from equities to futures markets following the closure of the underlying market. This paper examines the impact of the extension of trading hours in Hang Seng Index futures traded on the Hong Kong Futures Exchange on the 20 November, 1998 to 15 minutes after the close of the underlying market (the Stock Exchange of Hong Kong). Using the unique natural experiment provided by this change, a pattern similar to US markets is documented for the Hang Seng Index Futures following the change in trading hours. This provides strong evidence that the intraday pattern in volatility is caused by market closure. Unlike US futures exchanges, price reporters on the floor of the Hong Kong Futures Exchange collect quote data in addition to trade data. This data facilitates a test of another plausible microstructure explanation for the observed behaviour–bid–ask bounce associated with trading activity. This paper provides evidence that bid–ask bounce also explains part of the observed intraday behaviour in price volatility.     

The Influence of Information Arrival on Market Microstructure: Evidence from Three Related Markets

This study examines the influence of information arrival on market microstructure for the MMI, NYSE, and S&P 500 stock index futures markets, with special emphasis on the effects of opening and closing of trading and expiration of contracts on price movements and trading activities. The results of the examination show that although the opening of the (MMI) futures market is associated with higher volatility, it is when the spot market opens that volatility reaches its highest level. Similarly, the closing of the futures markets, though more volatile, is not as volatile as the closing of the spot markets. Trading patterns, on the other hand, are distinct from volatility. For MMI, trading declines consistently after the close of the spot market. In contrast, the NYSE and S&P 500 continue to trade and reach a peak at the close of the futures markets. Expiration effects are evidenced by the increase in volatility and trading near the closing of the MMI and the spillover to the NYSE and S&P 500. In sharp contrast, the expirations of the NYSE and S&P 500 are only assooiated with decrease in trading, suggesting that efforts to dampen volatility by changing expiration days from Friday to Thursday and shifting settlement price from Friday close to Friday open, have been successful.     

Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis

The relationship between trading volume and volatility in foreign exchange markets continues to be of much interest, especially given the higher than expected volatility of returns. Allowing for nonlinearities, this paper tests competing hypotheses on the possible relationship between volatility and trading volume using data for three major currency futures contracts denominated in US dollars, namely the British pound, the Canadian dollar and the Japanese yen. We find that trading volumes and return volatility are negatively correlated, implying a lack of support for the mixture of distributions hypothesis (MDH). Using linear and nonlinear Granger causality tests, we document significant lead-lag relations between trading volumes and return volatility consistent with the sequential arrival of information (SAI) hypothesis. These findings are robust and not sample-dependent or due to heterogeneity of beliefs as proxied by open interest. Furthermore, our results are insensitive to the modeling approach used to recover volatility measures. Overall, our findings support the contention that short- to medium-term currency relationships may be dominated by trading dynamics and not by fundamentals.     

Intraday and interday volatility in the Japanese stock market

This paper characterizes the volatility in the Japanese stock market based on a 4-year sample of 5-min Nikkei 225 returns from 1994 through 1997. The intradaily volatility exhibits a doubly U-shaped pattern associated with the opening and closing of the separate morning and afternoon trading sessions on the Tokyo Stock Exchange. This feature is consistent with market microstructure theories that emphasize the role of private and asymmetric information in the price formation process. Meanwhile, readily identifiable Japanese macroeconomic news announcements explain little of the day-to-day variation in the volatility, confirming previous findings for US equity markets. Furthermore, by appropriately filtering out the strong intradaily periodic pattern, the high-frequency returns reveal the existence of important long-memory interdaily volatility dependencies. This supports recent results stressing the importance of exploiting high-frequency intraday asset prices in the study of long-run volatility properties of asset returns.     

Investor Sentiment,Trading Behavior and Informational Efficiency in Index Futures Markets

This paper shows that traders in index futures markets are positive feedback traders—they buy when prices increase and sell when prices decline. Positive feedback trading appears to be more active in periods of high investor sentiment. This finding is consistent with the notion that feedback trading is driven by expectations of noise traders. Consistent with the noise trading hypothesis, order flow in index futures markets is less informative when investors are optimistic. Transitory volatility measured at high frequencies also appears to decline in periods of bullish sentiment, suggesting that sentiment‐driven trading increases market liquidity.     

On the Role of Futures Trading in Spot Market Fluctuations: Perpetrator of Volatility or Victim of Regret?

We examine the role of index futures trading in spot market volatility. We use the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) approach to measure volatility, analyze causality and feedback relations between volatilities in the spot and futures markets, and test various hypotheses in the context of a multivariate model that incorporates other macrostate variables. Our empirical results suggest index futures trading may not be blamed for the observed volatility in the spot market. Rather, we find stronger and more consistent support for the alternative posture that volatility in the futures market is an outgrowth of a turbulent cash market. We use the regret (cognitive dissonance) theory to explain our results.     

Dynamic spillover effects in futures markets: UK and US evidence

Previous studies on spillover effects in futures markets have so far confined themselves to static analyses. In this study, we use a newly introduced spillover index to examine dynamic spillovers between spot and futures markets volatilities, volume of futures trading and open interest in the UK and the US. Based on a dataset over the period February 25, 2008 to March 14, 2013, that encompasses both the global financial crisis and the Eurozone debt crisis, we find that spot and futures volatilities in the UK (US) are net receivers (net transmitters) of shocks to volume of futures trading and open interest. The analysis also sheds light on the dynamic interdependence of spot and futures markets volatilities between the US and the UK. Specifically, the spot and futures volatility spillovers between the UK and US markets are of bidirectional nature, however, they are affected by major economic events such as the global financial and Eurozone debt crises. Several robustness checks endorse our main findings. Overall, these results have important implications for various market participants and financial sector regulators.     

Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis

We study the simultaneity impact of the European Central Bank news on the daily realized volatility transmission mechanism (spillovers) among various US spot and futures markets. To this end, we apply a bias-corrected vector autoregressive model via Wild bootstrap simulation. We use minute-by-minute intraday data to construct daily realized volatility. We consider 429 news form the ECB as important events employing two major classifications, namely, a country classification with the highest total number of days related ECB news and a type of ECB news classification. We find that investors in futures markets react more vigorously and mainly for the ECB news that is associated with the group of EMU member states applied structural reforms. Yet, more importantly, we show that the US stock markets response heterogeneously to the ECB news, as we find key disagreements in the reactions both across the US markets and the types of ECB news studied. Such evidence is consistent with the explanation of the differential interpretation of information among market participants. From a practical point of view, we suggest that investors in the US spot market can effectively use two or more futures contracts to minimize their exposure to volatility risk associated with that news.     

Circuit Breakers,Trading Collars,and Volatility Transmission Across Markets: Evidence from NYSE Rule 80A

The NYSE's Rule 80A attempted to delink the futures and equity markets by limiting index arbitrage trades in the same direction as the last trade to reduce stock market volatility. Rule 80A leads to a small but statistically significant decline in intraday U.S. equity market volatility. In addition, the results are asymmetric: volatility is dampened more in a rising market than in a declining one. These results suggest that, to a limited extent, rule restrictions on trading can sufficiently delink the futures and equity markets enough to reduce the transmission of volatility.     

Information transfer,microstmctures and intraday price return spikes

Previous research has identified overnight public information as the cause of higher opening returns and mean reversion in security markets. This paper tests this hypothesis by using an intervention and transfer function time series model to filter out the dynamic effects of an overnight information set on the opening, and subsequent, intraday AOI stock and SPI futures intraday price returns. A further research objective was to analyse the process by which information is transferred into prices and whether there is a differential impact across stock and futures markets. It was determined that the information contained in the overnight US stock market had: (i) a differential impact on the Australian stock and futures market, and (ii) after filtering out the impact of overnight information, a significant reversal tendency remained in both markets after opening. Further analysis supported the conclusion that price spikes at opening were not wholly related to overnight information. Other possible explanations, such as different trading mechanisms, did not provide a satisfactory explanation. Overall, it appears that the uncertainty participants face at the beginning of a trading session may induce a number of subtle market reactions (both rational and irrational), in markets with different microstmctures and trading clientele.     

Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis

This paper models the relationship of European Union Allowance spot- and futures-prices within the second commitment period of the European Union emissions trading scheme. Based on high-frequency data, we analyze the transmission of information in first and second conditional moments. To reveal long-run price discovery, we compute common factor weights of Schwarz and Szakmary (1994) and information shares of Hasbrouck (1995) based on estimated coefficients of a VECM. To analyze the short-run dynamics, we perform Granger-causality tests. We identify the futures market to be the leader of the long-run price discovery process, whereas the informational role of the futures market increases over time. In addition, we employ a version of the UECCC-GARCH model as introduced by Conrad and Karanasos (2010) to analyze the volatility transmission structure. The volatility analysis indicates a close relationship between the volatility dynamics of both markets, whereas in particular we observe spillovers from the futures to the spot market. As a whole the investigation reveals that the futures market incorporates information first and then transfers the information to the spot market.     

Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect

Future markets play vital roles in supporting economic activities in modern society. For example, crude oil and electricity futures markets have heavy effects on a nation’s energy operation management. Thus, volatility forecasting of the futures market is an emerging but increasingly influential field of financial research. In this paper, we adopt big data analytics, called Extreme Gradient Boosting (XGBoost) from computer science, in an attempt to improve the forecasting accuracy of futures volatility and to demonstrate the application of big data analytics in the financial spectrum in terms of volatility forecasting. We further unveil that order imbalance estimation might incorporate abundant information to reflect price jumps and other trading information in the futures market. Including order imbalance information helps our model capture underpinned market rules such as supply and demand, which lightens the information loss during the model formation. Our empirical results suggest that the volatility forecasting accuracy of the XGBoost method considerably beats the GARCH-jump and HAR-jump models in both crude oil futures market and electricity futures market. Our results could also produce plentiful research implications for both policy makers and energy futures market participants.     

The dynamics of volatility transmission and information flow between ADRs and their underlying stocks

This research examines the dynamics of volatility transmission and information flow between ADRs and the underlying stocks. Using a bivariate GARCH model with BEKK parameterisation, the study investigates how changes in volatility in the ADR market affect the volatility in the underlying equity market and vice versa. The findings suggest a bidirectional volatility transmission and information flow between the ADR and underlying stock markets. ADRs and underlying stocks respond to their own innovations as well as to the innovations in each other's market. The findings are consistent for all countries in the sample as well as for different sub-periods. The evidence suggests that the differences in synchronicity of trading period between the US market and other developed markets included in the sample has had no effect on the volatility transmission and information flow between ADRs and underlying stocks.     

The dynamic relationship of volatility,volume, and market depth in currency futures markets

This study examines the dynamic interactions among return volatilities, volume, and market depth for five currency futures markets. We use vector autoregressive analysis (VAR) to identify not only the nature of these relations but also the direction and speed of the information flow between variables. We find that return volatility is subject to strong reversal effects from trading volume and market depth. The results also indicate that the volatility appears to have predictive power on volume but not on market depth. Furthermore, this study finds that volume and depth are not endogenously determined, as their lead–lag relationship is asymmetrical. We also observe an increasing trend of integration between offshore and domestic information that affects the movement of currency futures prices.     

Exchange traded currency derivatives markets in India: the road ahead

Indian exchanges have recently been permitted to offer currency futures on their platforms to the market participants. The paper outlines the contract, and charts the development and growth of currency futures in India since their inception in 2008. It emphasizes the existing close connectivity between commodity and currency markets. It highlights the increased exchange rate volatility of Indian exchange rate against US dollar (INRUSD) during conventional and non conventional trading hours and argues for the ability of the market to quickly adapt to extended trading hours. The paper recommends some new products and an alternative mechanism to settle the contracts.