Mean-variance hedging with oil futures

Wang, Liao; Wissel, Johannes

doi:10.1007/s00780-013-0203-x

Cited by 5 publications

(9 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ec25 where x t , y t and z t above are deterministic functions; the linearity comes from Y t , which also follows a linear SDE (see ( 28)), as well as from η t in (31), which is linear in Y t . Now, Lemma A.4 in Wang and Wissel (2013) immediately applies, and we conclude that J t /Z t is a martingale under P M . Next,…”

Section: What Remains Is To Showmentioning

confidence: 60%

“…We remark that χ T (A X ) is closed in L 2 (P); refer to Lemma 2.6 and Theorem 2.8 of Černỳ and Kallsen (2008); and for a brief review on this, refer to Theorem A.1 of Wang and Wissel (2013).…”

Section: Ec51 Technical Preparationmentioning

confidence: 99%

“…, hence it is sufficient to find a sequence of elements in this set, with limit (in L 2 (P)) as Z M T − Z M 0 , then the desired result will follow from the closedness. To do this, we follow the approach similar to that in the proof of Theorem 3.5 in Wang and Wissel (2013). Define the sequence of G t -stopping times:…”

Section: Now We Proceed With Showing Zmentioning

confidence: 99%

See 2 more Smart Citations

How Does Risk Hedging Impact Operations? Insights from a Price-Setting Newsvendor Model

Wang¹,

Ye²,

Zhang³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

Financial asset price movement impacts product demand and thus influences operational decisions of a firm. We develop and solve a general model that integrates financial risk hedging into a price-setting newsvendor. The optimal hedging strategy is found analytically, which leads to an explicit objective function for optimization of pricing and service levels. We find that, in general, the presence of hedging reduces the optimal price. It also reduces the optimal service level when the asset price trend positively impacts product demand ("asset price benefits demand"), while it may increase the optimal service level by a small margin when the impact is negative ("asset price hurts demand"). We construct the mean-variance efficient frontier that characterizes the risk-return trade-off, and we quantify the risk reduction achieved by the hedging strategy. Our numerical case study using real data of Ford Motor Company shows that the markdown in price and decrease in service level are small under our model, and the hedging strategy substantially reduces risk without materially reducing operational profit.

show abstract

Section: What Remains Is To Showmentioning

confidence: 60%

Section: Ec51 Technical Preparationmentioning

confidence: 99%

See 1 more Smart Citation

How Does Risk Hedging Impact Operations? Insights from a Price-Setting Newsvendor Model

Wang¹,

Ye²,

Zhang³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…They then construct a portfolio of options (and the underlying) as a hedging strategy. Wang and Wissel (2013) study mean-variance hedging of price risk born by kerosene consumers (or producers) with pre-specified consumption (or production) in a continuous-time setting using crude oil futures. Kouvelis et al (2013) consider a model that is similar to Wang and Wissel (2013): optimization under the mean-variance criterion, and financial hedging is in the setting of producing or storing a commodity that can be used to supply customer demand.…”

Section: Related Literaturementioning

confidence: 99%

“…They then construct a portfolio of options (and the underlying) as a hedging strategy. Wang and Wissel (2013) study mean‐variance hedging of price risk born by kerosene consumers (or producers) with pre‐specified consumption (or production) in a continuous‐time setting using crude oil futures. Kouvelis et al.…”

Section: Introductionmentioning

confidence: 99%

Risk Hedging for Production Planning

Wang

Yao

2021

Production and Operations Management

Self Cite

View full text Add to dashboard Cite

T raditional production planning is primarily a quantity or capacity decision, which must be made at the beginning of a planning horizon before production starts. Adding to this decision a real-time control, a risk-hedging strategy carried out throughout the horizon can better mitigate the risk involved in demand volatility. We demonstrate how this can be done in terms of jointly optimizing the capacity and the hedging decisions, addressing both the mean-variance and the shortfall objectives. Solution techniques, results, and insights are highlighted. In particular, we illustrate that our approach readily accommodates data analytics and explicitly quantifies the improvement to the efficient frontier contributed by hedging.

show abstract

Production with Risk Hedging—Optimal Policy and Efficient Frontier

Wang

Yao

2017

Operations Research

View full text Add to dashboard Cite

Demand for many products may depend on the price of a tradable asset or on the economy in general. For example, demand for equipment that plants or harvests corn correlates with the corn price on the commodity market, and discount stores experienced increased sales revenue during the last recession. Thus, we model demand as a stochastic process with two components: in addition to the usual Gaussian component reflecting demand volatility, there is a drift component taking the form of a function of a tradable asset price. (In the case of dependence on the general economy, the asset price can be a broad market index, such as the S&P 500 Index.) With this demand model, we study the one-time production quantity decision along with a real-time risk-hedging strategy over a given planning horizon (the production cycle). Pursuing a mean-variance formulation, we derive the optimal solution to both production and hedging decisions. We give a complete characterization of the efficient frontier and quantify the improvement in risk-return trade-off achieved by the hedging strategy. Furthermore, we show that the hedging strategy is self-financing in the sense that the expected total wealth from both production and hedging stays nonnegative at all times. The online appendix is available at https://doi.org/10.1287/opre.2017.1597

show abstract

Mean-variance hedging with oil futures

Cited by 5 publications

References 23 publications

How Does Risk Hedging Impact Operations? Insights from a Price-Setting Newsvendor Model

How Does Risk Hedging Impact Operations? Insights from a Price-Setting Newsvendor Model

Risk Hedging for Production Planning

Production with Risk Hedging—Optimal Policy and Efficient Frontier

Contact Info

Product

Resources

About