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The purpose of this paper is to derive a new option pricing model for options on futures calendar spreads. Calendar spread option volume has been low and a more precise model to price them could lead to lower bid-ask spreads as well as more accurate marking to market of open positions.

The new option pricing model is a two-factor model with the futures price and the convenience yield as the two factors. The key assumption is that convenience follows arithmetic Brownian motion. The new model and alternative models are tested using corn futures prices. The testing considers both the accuracy of distributional assumptions and the accuracy of the models’ predictions of historical payoffs.

Panel unit root tests fail to reject the unit root null hypothesis for historical calendar spreads and thus they support the assumption of convenience yield following arithmetic Brownian motion. Option payoffs are estimated with five different models and the relative performance of the models is determined using bias and root mean squared error. The new model outperforms the four other models; most of the other models overestimate actual payoffs.

The model is parameterized using historical data due to data limitations although future research could consider implied parameters. The model assumes that storage costs are constant and so it cannot separate between negative convenience yield and mismeasured storage costs.

The over 30-year search for a calendar spread pricing model has not produced a satisfactory model. Current models that do not assume cointegration will overprice calendar spread options. The model used by the Chicago Mercantile Exchange for marking to market of open positions is shown to work poorly. The model proposed here could be used as a basis for automated trading on calendar spread options as well as marking to market of open positions.

The model is new. The empirical work supports both the model’s assumptions and its predictions as being more accurate than competing models.

This study explores the arbitrage profitability of the KOSPI200 futures spread, using intraday data during 10 days prior to the expiration day of each contract for the 9/3/2001 ∼ 6/912005 period. The theoretical frameworks for arbitrage strategies were developed for the analysis. Our results show that 97.36% of the total 8.633 observations were fairly priced. 1.46% (126 observations) were underpriced, and 1.18% (102 observations) were overpriced, in the ex post arbitrage profitability analysis between the futures spread and the calendar spread. Also, in the arbitrage profitability analysis based on the mispricing of the KOSPI200 futures spread against the theoretical price. 90.39% of the total 10.054 observations were fairly priced and 9.61 % (966 observations) were underpriced. There was no overpriced observation. The ajority of those underpriced observations were concentrated in the 3rd Quarter of 2001 and the 1st quarter of 2003. Overall, there were very few arbitrage opportunities except for the introductory period and some contracts with high uncertainty, implying that the KOSPI200 futures spread market has been generally efficient.

The case deals with risk management issues related to a large calendar spread position in a highly seasonal and volatile commodity (natural gas). Apart from fundamental factors affecting the supply and demand for natural gas, the spread is also exposed to transient price movements in the futures market itself. The case is designed to be used in courses on derivatives, alternative investments and hedge funds.

In early January 2008, a senior VP with LAAMCO, a fund of hedge funds known for alternative investments, was conducting due diligence on an equity market-neutral hedge fund. The hedge fund used an option strategy known as a collar (also known as a bull spread or split-strike conversion). The track record of the hedge fund had been stellar. The fund's performance had not only beaten that of the S&P 500 Index over the same period but had done so with much lower monthly return volatility. As part of the due diligence, it was necessary to backtest the collar strategy and try to quantify how much value the manager, BLM Investment Securities, LLC, (BLM) had added. The case is a disguised representation of an actual hedge fund—the true identity of BLM is revealed to students at the end of the case discussion.

The purpose of this paper is to identify possible tax synergies from acquisitions when the acquiring firm gains a non‐debt tax shield (NDTS) not directly associated with its own past performance, or a windfall NDTS. One possible benefit of a windfall NDTS is reduced reliance on interest tax shields to lower the firm's marginal tax rate (MTR).

This paper tests the likelihood of issuing debt following acquisitions of windfall non‐debt tax attributes with logistic regressions. Both acquirers and targets are publicly held US firms. Acquisitions are completed from 1987 to 2003, and debt issues are observed following the deal. Target firm tax attributes are defined as the total tax spread, tax loss carryforward (TLCF), and the MTR.

Target firm tax spread and TLCFs are inconsequential to the acquirer's likelihood of issuing future debt, suggesting that tax synergies are relatively unimportant motives for acquisitions. As predicted, the target firm MTR is not significant to acquirer debt issues.

This paper makes several contributions. First, the notion of tax synergies from acquisitions is unresolved. This paper continues the search for tax synergies in acquisitions by examining the importance of acquired NDTS in the post‐acquisition period. Second, this paper examines the influence of NDTS on debt issuance in a post‐event framework. Third, this paper provides additional evidence that corporate managers have leverage targets.

This article discusses static hedges for installment options, which are finding broad application in cases where the option‐buyer may reduce up‐front premium costs via early termination of an option. An installment option is a European option in which the premium, instead of being paid up front, is paid in a series of installments. If all installments are paid, the holder receives the exercise value, but the holder has the right terminate payments on any payment date, in which case the option lapses with no further payments on either side. The authors summarize pricing and risk management concepts for these options, in particular, using static hedges to obtain both no‐arbitrage pricing bounds and very effective hedging strategies with almost no vega risk.

Motivated by the debate on the patterns and sources of commodity futures returns, this paper investigates the performance of three investment trading strategies, namely, the momentum strategy of Jegadeesh and Titman (1993), the 52-week high momentum strategy of George and Hwang (2004) and the pairs trading strategy of Gatev et al. (2006) in the commodity futures market.

The three strategies are those given by Jegadeesh and Titman (1993), George and Hwang (2004) and Gatev et al. (2006), respectively.

The authors find that there is no significant reversal profit across 189 formation-holding windows for all the three strategies. However, there are statistical and economically significant momentum profits, and the profitability increases with the rising of formation-holding periods. Momentum returns are quite sensitive to market conditions but the crash of momentum returns is partly predictable. Return seasonality, risk and herding also provide partial explanation of the momentum profits.

The authors are the first to compare the performances of the pairs trading strategy of Gatev et al. (2006), the conventional momentum of Jegadeesh and Titman (1993), and the 52-week high momentum of George and Hwang (2004) under 189 formation-holding windows. Also, the authors are the first to investigate the association between herding behaviour and momentum returns in the commodity futures market.

This paper aims to present a collaborative mashup platform for dynamic integration of heterogeneous data sources. The platform encourages sharing and connects data publishers, integrators, developers and end users.

This approach is based on a visual programming paradigm and follows three fundamental principles: openness, connectedness and reusability. The platform is based on semantic Web technologies and the concept of linked widgets, i.e. semantic modules that allow users to access, integrate and visualize data in a creative and collaborative manner.

The platform can effectively tackle data integration challenges by allowing users to explore relevant data sources for different contexts, tackling the data heterogeneity problem and facilitating automatic data integration, easing data integration via simple operations and fostering reusability of data processing tasks.

This research has focused exclusively on conceptual and technical aspects so far; a comprehensive user study, extensive performance and scalability testing is left for future work.

A key contribution of this paper is the concept of distributed mashups. These ad hoc data integration applications allow users to perform data processing tasks in a collaborative and distributed manner simultaneously on multiple devices. This approach requires no server infrastructure to upload data, but rather allows each user to keep control over their data and expose only relevant subsets. Distributed mashups can run persistently in the background and are hence ideal for real-time data monitoring or data streaming use cases. Furthermore, we introduce automatic mashup composition as an innovative approach based on an explicit semantic widget model.