Price limits,margin requirements,and default risk

This article investigates whether price limits can reduce the default risk and lower the effective margin requirement for a self‐enforcing futures contract by considering one more period beyond Brennan’s (1986) model to take into account the spillover of unrealized residual shocks due to price limits. The results show that, when traders receive no additional information, price limits can reduce the margin requirement and eliminate the default probability at the expense of a higher liquidity cost due to trading interruptions. Consequently, the total contract cost is higher than of that without price limits. When traders receive additional signals about the equilibrium price, we find that the optimal margin remains unchanged with or without the imposition of price limits, a result that is in conflict with Brennan’s assertion. Hence, we conclude that price limits may not be effective in improving the performance of a futures contract. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:573–602, 2000     

The effectiveness of coordinating price limits across futures and spot markets

We extend the work of Brennan ( 1986 ) to investigate whether the imposition of spot price limits can further reduce the default risk and lower the effective margin requirement for a futures contract that is already under price limits. Our results show that spot price limits do indeed further reduce the default risk and margin requirement effectively. In addition, the more precise the information is that comes from the spot market, the more the spot price limit rule constrains the information available to the losing party. The default probability, contract costs, and margin requirements are then lowered to a greater degree. Furthermore, for a given margin, both spot price limits and futures price limits can partially substitute for each other in ensuring contract performance. The common practice of imposing equal price limits on both the spot and futures markets, though not coinciding with the efficient contract design, has a lower contract cost and margin requirement than that without imposing spot price limits. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:577–602, 2003     

Back to the future: Futures margins in a future credit default swap index futures market

The introduction of exchange‐traded credit default swap (CDS) index futures is eminent and this development in the credit market is the subject of this article. A theoretically appealing and practically implementable approach to computing accurate futures margins based on extreme value theory is suggested. The approach is then exemplified with a study of the increasingly popular iTraxx Europe CDS index market. Although this market is not organized through an exchange and is not a futures market, the empirical results together with an arbitrage argument nonetheless suggest margin levels in a future exchange‐traded CDS index futures market computed using extreme value theory to be superior to those computed using the traditional normal distribution or the actual historical distribution. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:85–104, 2007     

Optimal margin level in futures markets: Extreme price movements

Along with price limits and capital requirements, the margin mechanism ensures the integrity of futures markets. Margin committees and brokers in futures markets face a trade-off when setting the margin level. A high level protects brokers against insolvent customers and thus reinforces market integrity, but it also increases the cost supported by investors and in the end makes the market less attractive. This article develops a new method for setting the margin level in futures markets. It is based on “extreme value theory,” which gives interesting results on the distribution of extreme values of a random process. This extreme value distribution is used to compute the margin level for a given probability value of margin violation desired by margin committees or brokers. Extreme movements are central to the margin-setting problem, because only a large price variation may cause brokers to incur losses. An empirical study using prices of silver futures contracts traded on COMEX is also presented. The comparison of the extreme value method with a method based on normality shows that using normality leads to dramatic underestimates of the margin level. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 127–152, 1999     

The CBOE S&P 500 three‐month variance futures

In this article, we study the market of the Chicago Board Options Exchange S&P 500 three‐month variance futures that were listed on May 18, 2004. By using a simple mean‐reverting stochastic volatility model for the S&P 500 index, we present a linear relation between the price of fixed time‐to‐maturity variance futures and the VIX². The model prediction is supported by empirical tests. We find that a model with a fixed mean‐reverting speed of 1.2929 and a daily‐calibrated floating long‐term mean level has a good fit to the market data between May 18, 2004, and August 17, 2007. The market price of volatility risk estimated from the 30‐day realized variance and VIX² has a mean value of −19.1184. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:48–70, 2010     

Rational expectations and market efficiency in the U.S. live cattle futures market: The role of proprietary information

The role of proprietary information in forecasting and market efficiency in the U.S. live cattle futures market is investigated. Using a unique proprietary data source collected by a private firm, we test whether the initial estimates in the USDA Cattle on Feed Report and the Knight‐Ridder pre‐release forecasts are unbiased and efficient forecasts of final revised USDA Cattle on Feed Report numbers. We then use these results to test whether futures price movements are predictable based on information in the proprietary data. We also test whether the initial estimates from the Cattle on Feed Report have new information that moves prices once the information contained in the proprietary data source has been taken into account. Results suggest that the information contained in the proprietary data source does have statistically significant explanatory power for forecasting final revised Cattle on Feed Report numbers and for predicting short‐term price movements of futures contracts. The results are inconsistent with strong‐form market efficiency in the live cattle futures market. We also find that the initial estimates in the Cattle on Feed Report still have new information that moves prices even after accounting for the unique information in both the Knight‐Ridder pre‐release forecasts and the proprietary data. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:429–451, 2004     

Volatility and commodity price dynamics

Commodity prices are volatile, and volatility itself varies over time. Changes in volatility can affect market variables by directly affecting the marginal value of storage, and by affecting a component of the total marginal cost of production, the opportunity cost of producing the commodity now rather than waiting for more price information. I examine the role of volatility in short‐run commodity market dynamics and the determinants of volatility itself. I develop a structural model of inventories, spot, and futures prices that explicitly accounts for volatility, and estimate it using daily and weekly data for the petroleum complex: crude oil, heating oil, and gasoline. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1029–1047, 2004     

Modeling discontinuous periodic conditional volatility: Evidence from the commodity futures market

This paper examines a wide variety of models that allow for complex and discontinuous periodic variation in conditional volatility. The value of these models (including augmented versions of existing models) is demonstrated with an application to high frequency commodity futures return data. Their use is necessary, in this context, because commodity futures returns exhibit discontinuous intraday and interday periodicities in conditional volatility. The former of these effects is well documented for various asset returns; however, the latter is unique amongst commodity futures returns, where contract delivery and climate are driving forces. Using six years of high‐frequency cocoa futures data, the results show that these characteristics of conditional return volatility are most adequately captured by a spline‐version of the periodic generalized autoregressive conditional heteroscedastic (PGARCH) model. This model also provides superior forecasts of future return volatility that are robust to variation in the loss function assumed by the user, and are shown to be beneficial to users of Value‐at‐Risk (VaR) models. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:805–834, 2004     

On the adequacy of single‐stock futures margining requirements

Unlike the traditional futures contract risk‐based approach to margining, new security futures contracts are margined under a strategy‐based margining system similar to that which applies in the equity options markets. As a result, these new margin requirements are potentially much less sensitive to changes in market conditions. This article performs a simulation to evaluate whether these alternative margining methodologies can be expected to produce comparable outcomes. The analysis suggests that a 1‐day settlement period will likely lead to collection of customer margins that are virtually always greater than that which its traditional risk‐based counterpart would require. A 4‐day settlement period would lead to margin requirements that both significantly under‐ and overmargin relative to a comparable risk‐based system. This study argues that exchanges may approach the preferred probability of customer exhaustion by managing margin settlement intervals. Thus, the new strategy‐based rules, in and of themselves, will not necessarily inhibit new security futures trading activity. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:989–1002, 2003     

Comparing alternative assumptions on the term structure of futures prices: Reply

Donald Lien and Yan Wang (this issue) suggest an alternative test for different specifications of the term structure of futures prices, as used in our recently published paper in The Journal of Futures Markets. Our paper (Y. V. Veld‐Merkoulova and F. A. de Roon, 2003) focuses on developing optimal hedging strategies in case sufficiently long‐term futures contracts are not available (or not actively traded) on the exchange. One of the preliminary steps underlying this strategy was to compare linear and log‐linear term structures of futures prices in order to choose an appropriate specification. Although this is not the main issue of our paper, it is certainly important to use the correct econometric procedure in testing alternative model specifications. The results found by Lien and Wang do not contradict our conclusion that a linear term structure of futures yields is superior to a linear term structure of futures prices. However, as we point out here, the tests suggested by Lien and Wang are not without flaws. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1101–1104, 2004     

Intraday price formation and bid–ask spread components: A new approach using a cross‐market model

This study examines the intraday formation process of transaction prices and bid–ask spreads in the KOSPI 200 futures market. By extending the structural model of Madhavan, A., Richardson, M., and Roomans, M. ( 1997 ), we develop a unique cross‐market model that can decompose spread components and explain intraday price formation for the futures market by using the order flow information from the KOSPI 200 options market, which is a market that is closely related to the futures market as well as considered to be one of the most remarkable options markets in the world. The empirical results indicate that the model‐implied spread and the permanent component of the spread that results from informed trading tend to be underestimated without the inclusion of options market information. Further, the results imply that trades of in‐the‐money options, which have high delta values, generally incur a more adverse information cost component (the permanent spread component) of the futures market than those of out‐of‐the‐money options, which have relatively low delta values. Finally, we find that the adverse information cost component that is estimated from the cross‐market model exhibits a nearly U‐shaped intraday pattern; however, it sharply decreases at the end of the trading day. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark     

Information content of extended trading for index futures

The recent extension of trading hours for Hang Seng Index Futures provides an opportunity to examine whether extended futures trading contains useful information about spot returns. Using the weighted price contribution measure, we find that pre‐open futures trades are associated with significant price discovery. We extend the model from T. Hiraki, E. D. Maberly, and N. Takezawa (1995) and adjust for the existence of a pre‐open trading session and the overnight trading of cross‐listed shares in London. Our results indicate that extended trading for index futures contains useful information in explaining subsequent spot returns during the trading day. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:861–886, 2004     

Credit Risk Assessment and Relationship Lending: An Empirical Analysis of German Small and Medium‐Sized Enterprises*

We estimate a logit scoring model for the prediction of the probability of default by German small and medium‐sized enterprises (SMEs) using a unique data set on SME loans in Germany. Our scoring model helps SMEs to gain knowledge about their default risk, which can be used to approximate their risk adequate cost of debt. This knowledge is likely to lead to a detection of hold‐up problems that German SMEs might be confronted with in their bank relationships. Furthermore, it allows them to monitor their bank’s pricing behavior and it reduces information asymmetries between lenders and borrowers. Finally, it can influence their future financing decisions toward capital market‐based financing.     

Mean Reversion and the Comovement of Equilibrium Spot and Futures Prices: Implications from Alternative Data‐Generating Processes

The comovements of spot and futures prices are characterized by six binary variables, including the term structure curvature of futures prices. These variables are used to uniquely identify 48 possible comovement patterns. Among them, 24 cases are associated with mean reversion, which is defined as a state when spreads between futures and spot prices are shrinking. These pattern frequencies are then calculated on a daily basis with the futures prices of 10 commodities, including precious metal, agricultural, and financial commodities. The results are further compared to simulation output from three data‐generating processes: a bivariate pure random walk, a mixed random walk with first‐order autoregression (AR(1)), and an error‐correction representation. The mean‐reverting frequencies for all 10 commodities are about 50%. Around half of the time, spot and futures prices are moving toward each other, and the rest of the time they move in the same direction. The symmetry of these results implies that the existence of substantial shocks originated from futures markets; thus, this is consistent with the risk premium view of futures trading. Also, although all simulation models produce similar mean‐reversion frequencies, the patterns of comovements of spot and futures prices are different, and the price dynamics depend heavily on whether the market is dominant contango or backwardation. Furthermore, the error‐correction model outperforms the random‐walk model for agricultural commodities, and the mixed random walk with AR(1) is hardly distinguishable from the pure random walk. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:769–796, 2001     

The response of volume and returns to the information shocks in China's commodity futures markets

This study investigates the response of returns and volume to different information shocks in China's commodity futures markets using bivariate moving average representation (BMAR) and bivariate vector autoregression (BVAR) methodologies. Consistent with the conclusions from stock market studies that have used these methodologies, it is found that the informational/permanent components are the dominant components for returns movements, and the noninformational/transitory components are the dominant components for trading volume. It is also found that the market response of copper futures improved during the sample period, and the market responses of actively traded futures (copper and soybeans) are better than those of the less actively traded futures (aluminum and wheat). © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:893–916, 2005     

The Disappearing January/Turn of the Year Effect: Evidence From Stock Index Futures and Cash Markets

This study examines the returns, relative to the S&P 500, on cash indices and futures tracking smaller stocks around the turn of the year. While we control for volatility clustering, return autocorrelation in small stock indices, and other calendar effects, our main focus is the evolution of the turn of the year effect through time: in particular, whether the effect is smaller or takes place earlier subsequent to the introduction of the S&P Midcap and Russell 2000 futures in 1993. We find that evidence of a traditional turn of the year effect, in both cash and futures, is confined to the pre‐1993 period. Post‐1993, there are no abnormal returns during the turn of the year window as a whole. Interestingly, returns in this period remain high on the last trading day of December, but they are negative across the first five trading days of January. In addition, post‐1993, we often observe significant abnormal returns prior to the traditional turn of the year, i.e., in the pre‐Christmas and post‐Christmas windows. Taken together, our results suggest that market participants may be eliminating the turn of the year effect with the aid of two new futures contracts that are well suited to this purpose. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:755–784, 2004     

Revisiting the empirical estimation of the effect of margin changes on futures trading volume

This study revisits the empirical estimation of the effect of margin requirements on trading volume. Although theory suggests that margin requirements impose a cost to traders and will therefore likely reduce volume traded, empirical examinations have generally failed to find this association. The contention of this article is that the theory is correct, but empirical estimation has generally neglected to adjust margins for underlying price risk. After adjusting for risk, this analysis finds economically and statistically significant negative effects of margin requirements on trading volume as predicted by theory. This study examined 6 contracts over a 17‐year time period and found that financial futures contracts (gold, Dow Jones, and 10‐Year Treasury Notes) were considerably more sensitive to changes in margin requirements than agricultural futures (wheat, corn, and oats). © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:561–576, 2003     

Market efficiency among futures with different maturities: Evidence from the crude oil futures market

Although many studies have investigated market efficiency of spot and futures prices, that among futures with different maturities has not been studied extensively. In this study, market efficiency and unbiasedness among such futures are defined and the concept of “consistently efficient (or consistently efficient and unbiased) market within n‐month maturity” is introduced. According to this definition, market efficiency and unbiasedness among WTI futures with different maturities are tested using cointegration analysis, and short‐term market efficiency, using an error correction model and GARCH‐M‐ECM. The results show that WTI futures are consistently efficient within 8‐month maturity and consistently efficient and unbiased within 2‐month maturity. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:487–501, 2011     

The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS

This study examines factors affecting stock index spot versus futures pricing and arbitrage opportunities by using the S&P 500 cash index and the S&P 500 Standard and Poor's Depository Receipt (SPDR) Exchange‐Traded Fund (ETF) as “underlying cash assets.” Potential limits to arbitrage when using the cash index are the staleness of the underlying cash index, trading costs, liquidity (volume) issues of the underlying assets, the existence of sufficient time to execute profitable arbitrage transactions, short sale restrictions, and the extent to which volatility affects mispricing. Alternatively, using the SPDR ETF as the underlying asset mitigates staleness and trading cost problems as well as the effects of volatility associated with the staleness of the cash index. Minute‐by‐minute prices are compared over different volatility levels to determine how these factors affect the limits of S&P 500 futures arbitrage. Employing the SPDR as the cash asset examines whether a liquid tradable single asset with low trading costs can be used for pricing and arbitrage purposes. The analysis examines how long mispricing lasts, the impact of volatility on mispricing, and whether sufficient volume exists to implement arbitrage. The minute‐by‐minute liquidity of the futures market is examined using a new transaction volume futures database. The results show that mispricings exist regardless of the choice of the underlying cash asset, with more negative mispricings for the SPDR relative to the S&P 500 cash index. Furthermore, mispricings are more frequent in high‐ and mid‐volatility months than in low‐volatility months and are associated with higher volume during high‐volatility months. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1182–1205, 2008     

Optimal Futures Hedging Under Multichain Markov Regime Switching

Most of the existing Markov regime switching GARCH‐hedging models assume a common switching dynamic for spot and futures returns. In this study, we release this assumption and suggest a multichain Markov regime switching GARCH (MCSG) model for estimating state‐dependent time‐varying minimum variance hedge ratios. Empirical results from commodity futures hedging show that MCSG creates hedging gains, compared with single‐state‐variable regime‐switching GARCH models. Moreover, we find an average of 24% cross‐regime probability, indicating the importance of modeling cross‐regime dynamic in developing optimal futures hedging strategies. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:173–202, 2014