Revenue Risk Research Articles

Product differentiation: Key to Macau's gaming revenue growth

For a tourism destination, the purpose of revenue management is to maximise the amount and minimise the risk of tourism revenue. This paper demonstrates how Macau can maintain a stable gaming revenue growth via product differentiation in the face of competition from emerging gaming destinations in Asia. Macau has recently opened its gaming market by bringing in Las Vegas gaming operators. While the introduction of Las Vegas-style casinos should help modernise Macau's gaming industry, Macau's market advantage is being threatened by the proliferation of Las Vegas-style destinations in the region. This paper proposes a revenue management strategy for Macau. It suggests that Macau should distinguish itself from other competing destinations by providing differentiated gaming service products. Enhancing its traditional VIP room operations is an effective way to achieve this goal. Implementing such a revenue management strategy, Macau will be able to preserve its risk-taker market and minimise the revenue risk posed by upcoming competition in the region.

Privatization of Rail and Tram Services in Melbourne: What Went Wrong?

Melbourne’s urban rail and tram systems were privatized in 1999 using a concessioning or franchising model similar to that employed for British Rail in the 1990s. The Melbourne franchise agreements promised improved services, increased patronage, reduced government subsidies and no real increase in fares. However, within 2 years, it became apparent that these predictions had been over optimistic, and subsequent negotiations saw the departure of one of the three franchisees and a renegotiation of agreements with the remaining two operators leading to substantial increases in subsidy levels. The paper reviews the Melbourne privatization experience to assess the extent to which it has produced benefits, the reasons the original predictions were not met and the extent to which the problems were avoidable. It concludes that although the Melbourne franchises were expressly designed legally to transfer revenue risk to the private operators, they failed to achieve this as a matter of practicality.

Joint pricing-network design and stochastic traffic engineering to manage demand uncertainty

I will describe two networking models, together with their optimization techniques, that span several time scales. In the longest time scale, where the goal is capacity planning, I will describe the work of Bienstock, Raskina, Saniee and Wang that considers joint pricing and network design of optical transport networks. Technological innovations are yielding sharply decreasing unit costs. There is also empirical evidence that suggests that the elasticity of bandwidth demand to price is high. Integrating these features in a unified profit-maximizing model leads to a large- scale nonlinear optimization problem. In this work, efficient solution techniques are developed to maximize the carrier's net present value with respect to pricing strategies and investment decisions for technology acquisitions. In the work of Mitra and Wang the time scale is shorter, the network infrastructure is fixed, and a model for stochastic traffic engineering is given in which the optimization is with respect to bandwidth provisioning and route selection. Traffic demands are uncertain, and the objective is to maximize a risk-adjusted measure of network revenue that is generated by serving demands. Considerable attention is given to the appropriate measure of risk in the network model. Risk-mitigation strategies are also advanced. The optimization model, which is based on mean-risk analysis, enables a service provider to maximize a combined measure of mean revenue and revenue risk. The conditions under which the optimization problem is an instance of convex programming are obtained. The solution is shown to satisfy the stochastic efficiency criterion asymptotically. The efficient frontier, which is the set of Pareto optimal pairs of mean revenue and revenue risk, is obtained.

Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management

We present a stochastic traffic engineering framework for optimizing bandwidth provisioning and route selection in networks. The objective is to maximize revenue from serving demands, which are uncertain and specified by probability distributions. We consider heterogenous demands with different unit revenues and uncertainties. Based on mean-risk analysis, the optimization model enables a carrier to maximize mean revenue and contain the risk that the revenue falls below an acceptable level. Our framework is intended for off-line traffic engineering design, which takes a centralized view of network topology, link capacity, and demand. We obtain conditions under which the optimization problem is an instance of convex programming and therefore efficiently solvable. We also study the properties of the solution and show that it asymptotically meets the stochastic efficiency criterion. We derive properties of the optimal solution for the special case of Gaussian distributions of demands. We focus on the impact of demand uncertainty on various aspects of traffic engineering, such as link utilization, bandwidth provisioning and total revenue. The carrier's tolerance to risk is shown to have a strong influence on traffic engineering and revenue management decisions. We develop the efficient frontier, which is the entire set of Pareto optimal pairs of mean revenue and revenue risk, to aid the carrier in selecting an appropriate operating point.

Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management

Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management We present a stochastic traffic engineering framework for optimizing bandwidth provisioning and route selection in networks. Traffic demands are uncertain and specified by probability distributions, and the objective is to maximize a risk-adjusted measure of network revenue that is generated by serving demands. Considerable attention is given to the appropriate measure of risk in the network model. We also advance risk-mitigation strategies. The optimization model, which is based on mean-risk analysis, enables a service provider to maximize a combined measure of mean revenue and revenue risk. The framework is intended for off-line traffic engineering, which takes a centralized view of network topology, link capacity and demand. We obtain conditions under which the optimization problem is an instance of convex programming. We study the properties of the solution and show that it asymptotically meets the stochastic efficiency criterion.In our numerical investigations we illustrate the impact of demand uncertainty on various aspects of the optimally traffic engineered solutions. The service provider's tolerance to risk is shown to have a strong influence on the traffic engineering and revenue management decisions. We develop the efficient frontier, which is the set of Pareto optimal pairs of mean revenue and revenue risk, to aid the service provider in selecting its operating point.

Dynamics of international financial networks with risk management

In this paper, we develop an international financialnetwork model in which the sources of funds and the intermediaries are multicriteria decision-makers and are concerned with both net revenue maximization and risk minimization. The model allows for both physical as well as electronic transactions and considers three tiers of decision-makers who may be located in distinct countries and may conduct their transactions in different currencies. We describe the behaviour of the various decision-makers, along with their optimality conditions, and derive the variational inequality formulation of the governing equilibrium conditions. We then propose a dynamic adjustment process which yields the evolution of the financial flows and prices and demonstrate that it can be formulated as a projected dynamical system. We also provide qualitative properties including stability analysis results. Finally, we discuss a discrete-time algorithm which can be applied to track the dynamic trajectories and yields the equilibrium financial flows and prices. We illustrate both the modelling framework as well as the computational procedure with several numerical international financial network examples.

Equalization and Stabilization

The federal Equalization transfer program makes fiscal resources of have-not provinces depend on fiscal conditions in have provinces, which tends to destabilize provincial finances: the data show that equalized revenues of receiving provinces are more volatile than own-source revenues. But this reflects the revenue risks facing the aggregate of all provinces, which an equalization program cannot insure. Controlling for aggregate risk, I find that the program has a significant stabilizing effect on provincial finances. Nevertheless, some improvements in revenue-sharing through the program might be contemplated. For example, a return to a national average capacity standard, from the five-province standard which has been in place since 1982, would increase insurance for idiosyncratic shocks by about one-third.

Dynamics of International Financial Networks with Risk Management

In this paper, we develop an international financial network model in which the sources of funds and the intermediaries are multicriteria decision-makers and are concerned with both net revenue maximization and risk minimization. The model allows for both physical as well as electronic transactions and considers three tiers of decision-makers who may be located in distinct countries and may conduct their transactions in different currencies. We describe the behavior of the various decision-makers, along with their optimality conditions, and derive the variational inequality formulation of the governing equilibrium conditions. We then propose a dynamic adjustment process which yields the evolution of the financial flows and prices and demonstrate that it can be formulated as a projected dynamical system. We also provide qualitative properties including stability analysis results. Finally, we discuss a discrete-time algorithm which can be applied to track the dynamic trajectories and yields the equilibrium financial flows and prices. We illustrate both the modeling framework as well as the computational procedure with several numerical international financial network examples.

Risk perception analysis of BOT road project participants in India

Despite massive investment opportunities and the establishment of a framework for private sector participation in highway infrastructure development programmes in India, private investment (including foreign direct investment) in this sector is not up to the expected level. A high degree of risk exposure, disagreement on many risk issues among major stakeholders, and the absence of adequate government guarantees have been identified as some of the major reasons for this lukewarm response. This paper discusses the outcome of a risk perception analysis carried out to evaluate the risk criticality, risk management capability, risk allocation/sharing preference, and factors influencing risk acceptance of major stakeholders. A survey was conducted among senior project participants such as government officials, promoters, lenders and consultants of Indian BOT road projects. Eight types of risks have been identified as very critical in the Indian road sector under BOT set up with traffic revenue risk being the most critical. Though there is fair agreement among survey respondents with respect to the risk management capabilities of stakeholders, their preferences of allocations are divergent. The significant factors influencing the risk acceptance of each stakeholder are identified through regression analysis. The study reveals that the factors and their relative influence on the risk acceptance of stakeholders are considerably different.

A Note on Deductible Insurance and Production

This paper examines the optimal production decision of a firm facing revenue risk. We show that the purchase of actuarially fair deductible insurance unambiguously induces the firm to produce more if the firm is not only risk averse but also prudent. If the firm's perferences satisfy constant absolute risk aversion, buying actuarially unfair deductible insurance unambiguously enhances production should the positive loading factor be sufficiently small. When there are moral hazard problems in that the firm's output cannot be contracted upon, we show that the purchase of actuarially fair deductible insurance unambiguously induces the firm to produce more if the firm's utility function is quadratic.

Water and Private Sector Partnership: Case of Karachi, A Mega-City of Pakistan

Implementation of private sector partnership (PSP) into Karachi Water and Sewerage Board (KWSB) of Karachi, a mega-city of Pakistan, was studied. The assignment was categorized into three distinct phases: development of the most appropriate strategy for PSP; execution of the preparatory work for PSP; and implementation of the agreed program. The PSP strategy approved by Government of Sindh (GS) province was designed to ensure that ownership of assets remains in the public sector while the technical, commercial and financial needs of the system become the responsibility of the private operator. The PSP strategy also ensured that benefits of system improvement are devoted to the greatest number of customers. A legal and regulatory framework had also been developed to enable the induction of a private operator into the provision of water sewerage services, to define the role and powers of the regulator and of government, and the rights of customers along with the measures for their enforcement. Six institutes for the framing of regulations of the water sector were identified. An extensive marketing program had been revealed to develop market interest and build up profile of the project. Having a detailed study on different working models of PSP, concession type of contract was the choice to be favored since it has been the basis used in other developing countries. Public awareness campaign was carried out to mitigate the persistent fears and misconceptions which could range from simple apprehensions regarding increases in tariffs and water charges among ordinary consumers to concerns touching issues of national security and sovereignty. Role of government was set to share risks by providing for political, legislative, force majeure, currency risk, and guaranteeing buy out provisions for private operator. While the private operator was anticipated to take normal commercial risks such a bidding risk, market risk including revenue and construction risks for infrastructure investments. Phase I strategy of the partnership was successfully done and approved by the GS in 2000. The phase II included a detailed technical and financial feasibility evaluation of the concession contract is under progress and likely to be completed until mid of this year, and phase III, transfer of ownership, is scheduled by the end of this year. Exact out come of the PSP is still awaited to be public. First initiative in Karachi is to execute successfully since this will develop investors' confidence and interests and will play a role model for the water utilities to follow in other growing cities of Pakistan.

Pricing Analysis for Merrill Lynch Integrated Choice

In late 1998, Merrill Lynch and other full-service financial service firms were under assault. Electronic trading and the commoditization of trading threatened Merrill Lynch's value proposition—to provide advice and guidance through a financial advisor. Management decided to offer investors more choices for doing business with Merrill Lynch. A cross-functional team evaluated alternative product and service structures and pricing and constructed models to assess individual client's behavior. The models showed that revenue at risk to Merrill Lynch ranged from $200 million to $1 billion. The resulting Integrated Choice strategy enabled Merrill Lynch to seize the marketplace initiative, changed the financial services landscape, and mitigated the revenue risk. As of year-end 2000, client assets reached $83 billion in the new offer, net new assets to the firm totaled $22 billion, and incremental revenue reached $80 million.

Risk Management in Agricultural Markets: A Review

AbstractThis article surveys and evaluates the current state of knowledge about producers' marketing strategies to manage price and revenue risk for farm commodities. The review highlights gaps between concepts and their implementation. Many well‐developed models of price behavior exist, but appropriate characterization and estimation of the probability distributions of commodity prices remain elusive. Hence, the preferred measure of price risk is ambiguous. Numerous models of optimal marketing portfolios for farmers have been specified, but their behavior appears to be inconsistent with most, if not all, of these models. In addition, some research suggests that farmers can earn speculative profits, which is inconsistent with notions of efficient markets. The conclusions discuss what academic research can and cannot accomplish in relation to assisting producers with risk‐management decisions. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:953–985, 2001

The revenue risk of value-based pricing for fed cattle: a simulation of grid vs. average pricing

The reluctance to adopt value-based pricing stems from a fundamental problem created by the system: increased revenue uncertainty and variability. The literature suggests that inconsistent carcass characteristics cause revenue variability under grid pricing. The possibility that the grid pricing structure, regardless of cattle quality variations, also causes revenue variability has been recognized but not fully analyzed. This study quantifies the impact of grid variability over time, pen quality differentials, and quality grade price discounts on average revenue per head for a pen of fed cattle. Grid pricing revenue results are compared to average pricing results.

The U.S. Federal Crop Insurance Program

The US. Federal Crop Insurance Program has evolved from a government‐run yield insurance program for wheat farmers to a public‐private partnership that provides a variety of yield and revenue insurance products to producers of over 100 different crops. US. policy‐makers continue to struggle with defining an appropriate role for the federal government in helping crop farmers manage revenue risk. New approaches using area‐yield or weather‐based options may hold promise for the future

Insurance and the behavior of competitive firms under revenue risks: a note

This paper re-examines the model of Ford, Mpuku, and Pattanaik [“Revenue Risks, Insurance, and the Behavior of Competitive Firms”.Journal of Economics 64 (1996): 233–246] wherein a risk-averse competitive firm faces insurable revenue risk. The optimal output and insurance cover of the firm are shown to be deterministically related in that the marginal costs of self-insurance and market insurance are equated. In response to increasing risk aversion, the firm always takes a higher insurance cover. Increasing fixed costs generate an income effect which induces the firm to take a higher insurance cover should the preference of the firm satisfy decreasing absolute risk aversion. Market insurance and self-insurance can be either substitutes or complements, depending on the shape of the variable insurance-premium schedule.

Optimal soil depletion with output and price uncertainty

This paper studies soil depletion incentives in a dynamic economic model under two different sources of revenue uncertainty (output and price risk). The focus is on the long-term effects of risk-averse preferences when farming decisions have implications for both expected short-run production and natural topsoil fertility. The analysis shows that the risk properties of the stock variable are crucial for the results arrived. The presence of risk preferences is found to improve soil conservation incentives in a low-input farming system, independent of the source of revenue risk considered. The only case for which soil conservation incentives are weakened is for high-input farming systems under price uncertainty.JEL classification: Q12, Q20, D81

Foreign exchange and revenue risks: analysis of key contract clauses in China's BOT project

Despite the Asian financial crisis, there was still growing international interests by sponsors in China's infrastructure projects financed on build-operate-transfer (BOT) concession contracts. With the closure of the Guangdong International Trust and Investment Corporation (GITIC), foreign banks have become cautious towards new loan applications by Chinese companies and they were confused about government support and guarantees. Therefore it is important to analyse and manage the unique or critical risks associated with China's BOT projects. This is especially so after new policies were introduced in late 1996 when the first state-approved BOT project, the US$650 million 2 X 350 megawatt coal-fired Laibin B Power Plant (Laibin B), was awarded. The findings are reported from an international survey on risk management of BOT projects, with emphasis on power projects in China, with a discussion of the adequacy of the key contract clauses used in the Laibin B's concession agreement (CA) in addressing the foreign exchange and revenue risks, which include exchange rate and convertibility risk, financial closing risk, dispatch constraint risk and tariff adjustment risk. Areas for improvements to these contract clauses are suggested.

Evaluation and management of foreign exchange and revenue risks in China's BOT projects

China is actively investigating ways to introduce project financing, specifically through the build-operate-transfer (BOT) scheme to meet the needs for the country's infrastructure and to be attractive to foreign investors and lenders. The advent of concession agreements, backed by new BOT laws, will be a positive move forward to achieving project-financed infrastructure projects. There are thus opportunities especially in the power sector for foreign investors. However, it is important to identify and manage the unique or critical risks associated with China's BOT projects. This is especially so after policies were introduced in late 1996 when the first state-approved BOT project, the US$650 million 2 × 350 megawatt (MW) coal-fired Laibin B Power Plant (Laibin B), was awarded. They include a competitive tendering process and 100% foreign ownership of the operating company. This paper is based on the findings from an international survey on risk management of BOT projects in developing countries, with emphasis on power projects in China. It discusses specifically the criticality of foreign exchange and revenue risks which include exchange rate and convertibility risk, financial closing risk, dispatch constraint risk and tariff adjustment risk. The measures for mitigating each of these risks are discussed also.

Optimum Crop Insurance under Joint Yield and Price Risk

ABSTRACT This article examines the design of an optimal policy for an insurable risk in the presence of another uninsurable risk. In the context of incomplete markets, indemnity payments are made whenever the insurable realized index is lower or higher than a critical level, depending on whether the policyholder's revenue increases or decreases with this index. These results are illustrated in an agricultural context in which crop insurance is available and price risk is uninsurable. Under the principle of increasing uncertainty, price risk induces the prudent producer to reduce his or her optimal price selection. The effect of direct subsidies on the optimal price selection is shown to depend on the producer's temperate behavior. INTRODUCTION Early literature on the theory of insurance, such as Borch (1962), Arrow (1971), and Raviv (1979), focused on optimal insurance purchasing in the context of a complete set of insurance markets for future risks. In recent years, the insurance-buying decision in incomplete markets has been examined when the insurable risk interacts in an additive manner with the uninsurable background risk, which can be correlated with the former (see Doherty and Schlesinger, 1983; Gollier, 1996). The purpose of this article is to investigate the optimal insurance policy when the indemnity is contingent only on an imperfect signal of the policyholder's revenue. More specifically, his or her random revenue is a function of an insurable random index and an independent background risk, which is assumed uninsurable. This source of uninsurability can stem from asymmetric information between insureds and insurers. In this context of incomplete markets, the design of an optimal insurance contract is derived. The optimal form depends on the effect of an increase in the insurable index on the policyholder's revenue. If the principle of increasing uncertainty (Leland, 1972) is satisfied and if the policyholder exhibits prudence (Kimball, 1990), an upper or lower bound associated with the slope of the optimal marginal coverage can be defined. Full insurance against the index is shown to be optimal if and only if the insurance premium is actuarially fair. These results are illustrated in an agricultural context in which the producer faces both yield and price uncertainty and in which a crop insurance market is available. Under a multiple peril crop insurance program, the producer selects a yield guarantee and a price selection at which a unit loss of output is compensated. The article first examines the effect of demand uncertainty on the optimal price selection and then analyzes how the payment of direct subsidies affects this price selection. To sign this effect, the concept of temperance introduced by Kimball (1992) is used. After the model has been presented in the next section, the design of an optimal insurance contract in the presence of background risk is derived. In the fourth section, these results are used to examine the producers' rationale for purchasing crop insurance when output price risk cannot be hedged. THE MODEL The problem of the insurance-purchasing decision of a risk-averse producer is considered in a static model. His or her revenue is based on an index, or a proxy, y, which is assumed insurable, and on a background risk [epsilon], which is assumed uninsurable. [1] The stochastic dependence between revenue risk and index risk is formalized by the deterministic revenue function R(y, [epsilon]), where [epsilon], where is independent of y and E([epsilon]) = 0, E denoting the expectation operator. The support of the cumulative distribution function associated with random variables y or [epsilon] is contained in [0, [y.sub.max]] or [[[epsilon].sub.min], [[epsilon].sub.max]] with [y.sub.max] [less than] 0 and [[epsilon].sub.min] [less than or equal to] 0 [less than or equal to] [[epsilon].sub.max], respectively. The revenue function is assumed strictly monotonic in the background risk and, without a loss of generality, a larger value of the [epsilon] risk generates a larger revenue; i. …