A multi-stage financial hedging approach for the procurement of manufacturing materials

Ni, Jian; Chu, Lap Keung; Wu, Feng; Sculli, D.; Shi, Yuan

doi:10.1016/j.ejor.2012.03.031

Cited by 19 publications

(14 citation statements)

References 21 publications

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“…Chiu and Choi (2016) buyers. See, e.g., Smith and Stulz (1985), Froot et al (1993), Neuberger (1999), Gaur and Seshadri (2005), Ni et al (2012Ni et al ( , 2016, and Kouvelis et al (2013). However, few researchers have considered the problem from the perspective of the other supply chain parties and/or the entire supply chain, with the possible exception of Caldentey and Haugh (2009) and Turcic et al (2015).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…We assume that there exists a futures contract written on the spot price of the same commodity used for production. In particular, we assume that the contract perfectly matches the planning horizon i.e., , which is a standard assumption in the hedging literature (see e.g., Ni et al (2012), Kouvelis et al (2013), Turcic et al 2015, Goel and Tanrisever (2017),…”

Section: Financial Marketmentioning

confidence: 99%

“…Following Ni et al (2012), this analysis is conducted by increasing or decreasing the demand variance by using a changing ratio, i.e.,…”

Section: Sensitivity Analysis Of the Changing Demand Variancementioning

confidence: 99%

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Buy now and price later: Supply contracts with time-consistent mean–variance financial hedging

Niu

Chu

et al. 2018

European Journal of Operational Research

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We consider a two-stage supply chain comprising one risk-neutral manufacturer (he) and one risk-averse retailer (she), where the manufacturer procures consumption commodities in spot market as major inputs for production and sells the final products to the retailer. The retailer then sells the final products to the market at a stochastic clearance price. We investigate a flexible price contract that allows the manufacturer to determine the product wholesale price, and the retailer to determine the order quantity, based on the future spot price of consumption commodities. Compared with the simple wholesale price contract, a win-win situation can be achieved under the flexible price contract when the manufacturer"s postponed processing cost is lower than a threshold. However, under this flexible price contract the retailer may suffer from the commodity price volatility, even if she does not procure the commodities directly. We further investigate how the risk-averse retailer conducts mean-variance financial hedging by purchasing consumption commodity futures contracts. We formulate the problem using a dynamic programming model and derive a

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Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Financial Marketmentioning

confidence: 99%

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Buy now and price later: Supply contracts with time-consistent mean–variance financial hedging

Niu

Chu

et al. 2018

European Journal of Operational Research

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“…The problem of bunker procurement risk hedging by trading bunker futures has been widely adopted in the container liner shipping industry. However, no research has considered this interesting area that has practical significance, although studies have been conducted on the general procurement risk-hedging problem (9-12) and on other commodities, such as electricity (13)(14)(15), natural gas (16), manufacturing materials (17), and agricultural products (18). Of all these studies, many deal with two-stage procurement, in which commodity derivatives (futures, options) contracts are signed at the first stage and are delivered and settled in cash at the second stage.…”

mentioning

confidence: 99%

Bunker Procurement Planning for Container Liner Shipping Companies

Meng

Wang

2015

Transportation Research Record: Journal of the Transportation R

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This paper investigates the bunker procurement planning (BPP) problem arising for a container liner shipping company that plans to purchase bunker from both bunker futures contracts and the spot market to hedge the risk in fluctuation of and increases in bunker prices. A multistage bunker procurement decision process for the BPP problem is developed to determine the monthly bunker procurement. The process allows the shipping company to sign bunker futures contracts in the first stage and to rebalance them in the subsequent stages. By assuming the stochasticity of bunker spot price, the BPP problem is formulated as a mean-variance minimization stochastic programming model. An approximation solution method for solving this model is designed by integrating random variable sampling technique, scenario tree generation, and quadratic programming approximation. Finally, numerical experiments demonstrate that bunker procurement risk can be effectively hedged with the proposed method. This study provides a useful decision tool for container liner shipping companies to use when planning bunker procurement.

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“…The criterion considered may be a combination of risk and return considerations. For instance, assuming that the option is exercised at date T, and denoting the option payoff and the value of the hedging portfolio at T by C T and V T , respectively, the following criteria, among others, have been proposed in the literature (see for instance Schweizer 1995;Follmer and Leukert 2000;Francois et al 2014;Hodges and Neuberger 1989;Ni et al 2012):…”

Section: Introductionmentioning

confidence: 99%

Global Hedging through Post-Decision State Variables

Breton

Godin

2017

JRFM

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Unlike delta-hedging or similar methods based on Greeks, global hedging is an approach that optimizes some terminal criterion that depends on the difference between the value of a derivative security and that of its hedging portfolio at maturity or exercise. Global hedging methods in discrete time can be implemented using dynamic programming. They provide optimal strategies at all rebalancing dates for all possible states of the world, and can easily accommodate transaction fees and other frictions. However, considering transaction fees in the dynamic programming model requires the inclusion of an additional state variable, which translates into a significant increase of the computational burden. In this short note, we show how a decomposition technique based on the concept of post-decision state variables can be used to reduce the complexity of the computations to the level of a problem without transaction fees. The latter complexity reduction allows for substantial gains in terms of computing time and should therefore contribute to increasing the applicability of global hedging schemes in practice where the timely execution of portfolio rebalancing trades is crucial.

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A multi-stage financial hedging approach for the procurement of manufacturing materials

Cited by 19 publications

References 21 publications

Buy now and price later: Supply contracts with time-consistent mean–variance financial hedging

Buy now and price later: Supply contracts with time-consistent mean–variance financial hedging

Bunker Procurement Planning for Container Liner Shipping Companies

Global Hedging through Post-Decision State Variables

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