Foreign Exchange Transaction Exposure in a Newsvendor Setting

Abstract In the global supply chain where there is a time lag between arrival of the shipment and the sale, the purchase price to the buyer may, on the day of settlement be different from that on the day of the order if the buyer is to pay in the supplier's currency. Either the supplier or the buyer is exposed to the loss due to exchange rate fluctuations. The key questions that arise then are: Does it matter who bears the risk? What aspect of exchange rate fluctuation affects the decisions of the supply chain partners? In this note related to Transaction Exposure, we show that in a classical newsvendor setting where the supplier has full information, the optimal policies are independent of which one of the two bears the risk. Numerical examples are presented to highlight model. This paper provides good scenarios in the case of risk management for manufacturer and retailer

Capacity Planning with Financial and Operational Hedging in Low‐Cost Countries

The authors of this paper outline a capacity planning problem in which a risk-averse firm reserves capacities with potential suppliers that are located in multiple low-cost countries. While demand is uncertain, the firm also faces multi-country foreign currency exposures. This study develops a mean-variance model that maximizes the firm’s optimal utility and derives optimal utility and optimal decisions in capacity and financial hedging size. The authors show that when demand and exchange rate risks are perfectly correlated, a risk- averse firm, by using financial hedging, will achieve the same optimal utility as a risk-neutral firm. In this paper as well, a special case is examined regarding two suppliers in China and Vietnam. The results show that if a single supplier is contracted, financial hedging most benefits the highly risk-averse firm when the demand and exchange rate are highly negatively related. When only one hedge is used, financial hedging dominates operational hedging only when the firm is very risk averse and the correlation between the two exchange rates have become positive. With both theoretical and numerical results, this paper concludes that the two hedges are strategic tools and interact each other to maximize the optimal utility

Joint optimal ordering and weather hedging contract decisions: a newsvendor model.

Yeung Yun Sing Samson.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 64-67).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 2 --- Background --- p.5Chapter 2.1 --- Applicability of Weather Derivative in Hong Kong: The Recre- ation Industry --- p.7Chapter 2.2 --- Types of Weather Risk --- p.9Chapter 3 --- Literature Review --- p.12Chapter 4 --- Basic Model --- p.17Chapter 4.1 --- Notations --- p.18Chapter 4.2 --- Assumptions --- p.21Chapter 4.3 --- The Profit Model --- p.22Chapter 5 --- Fundamental Analysis --- p.25Chapter 5.1 --- Sales Profit Analysis --- p.25Chapter 5.2 --- Option Analysis --- p.27Chapter 5.3 --- Profit Function Reformulation --- p.30Chapter 6 --- Objectivel: Lexicographic Optimization --- p.35Chapter 6.1 --- Equivalence between Lexicographic Optimization and Expected Utility Maximization --- p.38Chapter 6.2 --- Minimizing the Conditional Profit Variance given Q* --- p.39Chapter 6.3 --- Numerical Examples --- p.42Chapter 6.3.1 --- Convexity of conditional profit variance --- p.42Chapter 6.3.2 --- Correlation between Q* & N* --- p.47Chapter 7 --- Objective2: Mean-Variance Optimization --- p.52Chapter 7.1 --- Numerical Examples --- p.59Chapter 8 --- Conclusion and Future Work --- p.61Bibliography --- p.64Chapter A --- Weather Option Pricing --- p.68Chapter B --- Infeasibility of Perfect Hedge --- p.7

Buy Now and Price Later: Supply Contracts with Time-Consistent Mean-Variance Financial Hedging

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 closed-form time-consistent financial hedging policy. Through numerical experiments, we show that the commodity price risk from the manufacturer to the retailer is effectively mitigated with the hedging, and the benefits of the flexible price contract are maintained

The floating contract between risk-averse supply chain partners in a volatile commodity price environment

In this dissertation, two separate but closely related decision making problems in environments of volatile commodity prices are addressed. In the first problem, a risk-averse commodity user\u27s purchasing policy and his risk-neutral supplier\u27s pricing decision, where the user can purchase his needs through contract with his supplier as well as directly from the spot market, are analyzed. The commodity user is assumed to be the supplier\u27s sole client, and the supplier can always expand capacity, at a cost to the user, to accommodate the user\u27s demand in excess of initially reserved capacity. In the more generalized second problem, both parties (commodity user and supplier) are assumed to be risk averse, and both can directly access the spot market. In addition to making pricing decisions, the supplier is also faced with the challenge of establishing the right combination of in-house production and spot market engagements to manage her risk of exposure to spot price volatility under the contract. While the supplier has a frictionless buy and sell access to the spot market, the user can only access this market for buying purposes and incurs an access fee that is linearly increasing in the purchased volume. In both problems, by adopting the mean-variance criterion to reflect aversion to risk, the decisions of both parties are explicitly characterized. Based on analytical results and numerical studies, managerial insights as to how changes in the model\u27s parameters would affect each party\u27s decisions are offered at length, and the implications of these results to the manager are discussed. A focal point for the dissertation is the consideration of a floating contract, the landing price of which is contingent on the realization of the commodity\u27s spot market price at the time of delivery. It was found that if properly designed, not only can this dynamic pricing arrangement strategically position a long-term supplier against spot market competition, but it also has the added benefit of leading to improved supply chain expected profits compared to a locked-in contract price setting. Another key finding is that when making her pricing decisions, the supplier runs the risk of overestimating the commodity user\u27s vulnerability at higher levels of the user\u27s aversion to risk as well as at higher volatility of spot prices

Does hedging affect firm value? Evidence from Finland

This thesis analyses Nasdaq OMX Helsinki companies on how hedging affect firm value. The analysis bases its empirical part on theoretical literature and previous studies of the subject. The fundamental finance theory suggests that the ultimate measure of a com pany’s success is the firm value. Previous literature regarding on this subject proposes various ways to determine how hedging affect firm value and how different hedging strategies and instruments can be used to reduce various risks. World has globalized over the past years and doing so, it has also become a much more volatile environment. De rivatives have become more common, since they offer various ways to reduce different risks. At the same time, derivatives are facing a lot more regulation standards to avoid and reduce the possible risks on open large derivative positions. Since the derivative products have a quite large default risk, the value of derivatives as a risk management strategy has been questioned. For example, Warren Buffett (2002) declared that deriva tives are the financial weapons of mass destruction. This thesis tests the relation between hedging with financial derivatives and firm market value in companies that are listed in Nasdaq OMX Helsinki between the years 2014 and 2020 and therefore to contribute to the existing literature regarding on this subject. Ac cording to previous literature, Tobin’s Q has been proved to be an accurate measure for firm value, and therefore Tobin’s Q is used as a dependent variable for univariate and multivariate tests in this thesis. A new addition to this type of studies, Covid-19 rates are used as a control variable to test, if a firm value is affected more or less during Covid-19 pandemic. The results gained in this study suggests that hedging has a negative value premium. These results differ from some previous studies for example Allayannis & Weston (2001). However, the Finnish market is relatively small compared to U.S. markets and firm size has a huge effect in Finland regarding if the company is a hedger or a non-hedger. There fore, a larger international sample would be required to confirm the findings.Maailma on globalisoitunut merkittävästi 2000-luvun aikana. Samalla maailma on myös muuttunut entistä epävakaammaksi ja vaikeammin ennustettavaksi. Epävakaiden mark kinoiden vuoksi, myös johdannaisten käyttö on yleistynyt yritysmaailmassa niiden mah dollistamien erilaisten riskienhallintakeinojen vuoksi. Samaan aikaan johdannaisille on luotu paljon erilaisia säännöksiä, joiden avulla on voitu vähentää suurien johdannais positioiden aiheuttamaa riskiä. Johdannaisilla on itsessään kohtalaisen suuri vakioriski, jonka vuoksi johdannaisten käyttöä riskienhallinta välineenä on myös kritisoitu. Esimer kiksi Warren Buffett (2002) ilmoitti johdannaisten olevan rahoitusmaailman joukkotuho aseita. Tämän tutkielman tarkoituksena on tutkia kuinka suojautuminen johdannaisilla vaikut taa yrityksen arvoon. Tutkielmaan sisältyvät yritykset ovat Nasdaq OMX Helsingin pörs siin kuuluvia yrityksiä ajalta 2014–2020. Tutkielman empiirinen osuus pohjautuu aiem piin aiheesta tehtyihin tutkimuksiin ja kirjallisuuteen. Yrityksen arvoa pidetään perintei sen rahoituksen teorian mukaan parhaana mittarina yrityksen menestymiselle. Aihee seen liittyvä kirjallisuus pitää sisällään monia keinoja, kuinka johdannaisilla suojautumi nen vaikuttaa yrityksen arvoon, ja kuinka erilaisia suojautumisstrategioita ja erilaisia joh dannaisinstrumentteja voidaan käyttää vähentämään yrityksen kohtaamia riskejä. Aiemman kirjallisuuden perusteella on todettu, että yksi tarkin mittari yrityksen arvon mittaamiseen on Tobinin Q. Tämän vuoksi myös tässä tutkielmassa Tobinin Q toimii seli tettävänä muuttujana yksiulotteisissa ja moniulotteisissa analyyseissä. Tässä tutkiel massa uutena kontrollimuuttujana tämänkaltaisissa tutkimuksissa käytetään Covid-19 vuoden lukuja. Tämän kontrollimuuttujan avulla voidaan verrata, vaikuttaako suojautu minen Covid-19 pandemian aikana yrityksen arvoon enemmän tai vähemmän, kuin en nen pandemiaa. Tutkielman tulokset viittaavat siihen, että suojautumisella on negatiivi nen arvopreemio. Tulokset eroavat joistakin aiemmista tutkimuksista, esimerkiksi Al layannis & Weston (2001) mukaan suojautumisella on positiivinen arvopreemio. Suomen markkinat ovat kuitenkin huomattavasti pienemmät kuin Yhdysvaltojen ja esimerkiksi yrityksen koolla on valtava merkitys suomessa sille, onko yritys johdannaisten käyttäjä vai ei

Pricing decisions in a two-echelon decentralized supply chain using bi-level programming approach

Abstract Pricing is one of the major aspects of decision making in supply chain. In the previous works mostly a centralized environment is considered indicating the retailers cannot independently apply their decisions on the pricing strategy. Although in a two-echelon decentralized environment it may be possible that supply chain contributors have encountered with different market power situations which provide that some of them try to impose their interests in pricing and/or volume of the products. In such situations the leader-follower Stackelberg game or more specifically bi-level programming seems to be the best approach to overcome the problem. Furthermore, in this study we consider the impacts of disruption risk caused by foreign exchange uncertainty on pricing decisions in a multi-product two-echelon supply chain. Also it is assumed that the market is partitioned to domestic and international retailers with segmented market for each retailer. The purpose of this paper is to introduce decisions policy on the pricing such that the utility of both manufacturer and retailers is met. Since the proposed bi-level model is NP-hard, a simulated annealing method combining with Tabu search is proposed to solve the model. A numerical example is presented to investigate the effect of foreign exchange variation on the decision variables through different scenarios. The results from numerical example indicate that the international retailers are indifferent to the manufacture undergoes changes where the domestic retailers react to changes, dramatically

SUPPLY CHAIN RISK MANAGEMENT IN AUTOMOTIVE INDUSTRY

The automotive industry is one of the world\u27s most important economic sectors in terms of revenue and employment. The automotive supply chain is complex owing to the large number of parts in an automobile, the multiple layers of suppliers to supply those parts, and the coordination of materials, information, and financial flows across the supply chain. Many uncertainties and different natural and man-made disasters have repeatedly stricken and disrupted automotive manufacturers and their supply chains. Managing supply chain risk in a complex environment is always a challenge for the automotive industry. This research first provides a comprehensive literature review of the existing research work on the supply chain risk identification and management, considering, but not limited to, the characteristics of the automotive supply chain, since the literature focusing on automotive supply chain risk management (ASCRM) is limited. The review provides a summary and a classification for the underlying supply chain risk resources in the automotive industry; and state-of-the-art research in the area is discussed, with an emphasis on the quantitative methods and mathematical models currently used. The future research topics in ASCRM are identified. Then two mathematical models are developed in this research, concentrating on supply chain risk management in the automotive industry. The first model is for optimizing manufacturer cooperation in supply chains. OEMs often invest a large amount of money in supplier development to improve suppliers’ capabilities and performance. Allocating the investment optimally among multiple suppliers to minimize risks while maintaining an acceptable level of return becomes a critical issue for manufacturers. This research develops a new non-linear investment return mathematical model for supplier development, which is more applicable in reality. The solutions of this new model can assist supply chain management in deciding investment at different levels in addition to making “yes or no” decisions. The new model is validated and verified using numerical examples. The second model is the optimal contract for new product development with the risk consideration in the automotive industry. More specifically, we investigated how to decide the supplier’s capacity and the manufacturer’s order in the supply contract in order to reduce the risks and maximize their profits when the demand of the new product is highly uncertain. Based on the newsvendor model and Stackelberg game theory, a single period two-stage supply chain model for a product development contract, consisting of a supplier and a manufacturer, is developed. A practical back induction algorithm is conducted to get subgame perfect optimal solutions for the contract model. Extensive model analyses are accomplished for various situations with theoretical results leading to conditions of solution optimality. The model is then applied to a uniform distribution for uncertain demands. Based on a real automotive supply chain case, the numerical experiments and sensitivity analyses are conducted to study the behavior and performance of the proposed model, from which some interesting managerial insights were provided. The proposed solutions provide an effective tool for making the supplier-manufacturer contracts when manufacturers face high uncertain demand. We believe that the quantitative models and solutions studied in this research have great potentials to be applied in automotive and other industries in developing the efficient supply chains involving advanced and emerging technologies