A general unconstrained model for transfer pricing in multinational supply chains

Multinational supply chains operate in more than one country or tax jurisdiction and face decision problems concerned with trade flows of resources, products and services, transfer prices, and allocation of transport costs between their divisions. These decisions must consider, for the sake of optimality, corporate and governmental parameters such as the payment of dividends and royalties, ownership of and control over subsidiaries, income taxes differentials, duties and quotas, etc. In this paper, we generalize and extend the Theory of the Multinational Firm to the case of multinational supply chains. We propose a model that is more general and comprehensive than the previous ones proposed in the literature. To be more specific, our model integrates many of the previous research factors and includes new ones, such as transport costs and duty drawbacks, which are critical for supply chains that operate under international trade regulations. Under the maximization of the repatriated earnings objective, we study the optimality conditions of the corporate decision variables to derive managerial guidelines and to determine how decisions regarding trade quantities, transfer prices, and transport cost allocations affect the amount of taxes to be paid to host governments as well as the total after tax repatriated earnings of the corporation.     

A variational inequality arising from European option pricing with transaction costs

In this paper we present a method which can transform a variational inequality with gradient constraints into a usual two obstacles problem in one dimensional case.The prototype of the problem is a parabolic variational inequality with the constraints of two first order differential inequalities arising from a two-dimensional model of European call option pricing with transaction costs.We obtain the monotonicity and smoothness of two free boundaries.     

The stochastic transportation problem with single sourcing

We propose a branch-and-price algorithm for solving a class of stochastic transportation problems with single-sourcing constraints. Our approach allows for general demand distributions, nonlinear cost structures, and capacity expansion opportunities. The pricing problem is a knapsack problem with variable item sizes and concave costs that is interesting in its own right. We perform an extensive set of computational experiments illustrating the efficacy of our approach. In addition, we study the cost of the single-sourcing constraints.     

Investors’ preference for a positive tax rate depends on the level of the interest rate

In a financial market with only one stock, Cadenillas and Pliska (Financ Stoch 3:137–165, 1999) showed that sometimes investors can take advantage of a positive tax rate to maximize their portfolio return. Buescu et al. (Math Finance 17:477–485, 2007) generalized this surprising result to a market with one stock and one bank account with zero interest rate. We consider instead a financial market with one stock and one bank account with positive interest rate. As in the papers above, we assume that there are taxes and transaction costs in the financial market. We succeed in solving the problem of an investor who wants to maximize the long-run growth rate of his investment, even though the positivity of the interest rate increases the dimensionality of the problem and the difficulty of the computations. We characterize how the investors’ preference for a positive tax rate depends on the interest rate level: investors prefer a positive tax rate when the level of the interest rate is low, and the opposite occurs when the level of the interest rate is high. Most of the contributions of C. Buescu were made during his doctoral studies at the University of Alberta. The research of C. Buescu and A. Cadenillas was supported by the Social Sciences and Humanities Research Council of Canada grants 410-2003-1401 and 410-2006-1069. We are grateful to Stanley R. Pliska for comments and suggestions to a previous version of the paper, and to the associate editor and referees for constructive remarks. Existing errors are our sole responsibility.     

Volatility Targeting Using Delayed Diffusions

ABSTRACT

A target volatility strategy (TVS) is a risky asset-riskless bond dynamic portfolio allocation which makes use of the risky asset historical volatility as an allocation rule with the aim of maintaining the instantaneous volatility of the investment constant at a target level. In a market with stochastic volatility, we consider a diffusion model for the value of a target volatility fund (TVF) which employs a system of stochastic delayed differential equations (SDDEs) involving the asset realized variance. First we prove that under some technical assumptions, contingent claim valuation on a TVF is approximately of Black-Scholes type, which is consistent with and supports the standing market practice. In second place, we develop a computational framework using recent results on Markovian approximations of SDDEs systems, which we then implement in the Heston variance model using an ad hoc Euler scheme. Our framework allows for efficient numerical valuation of derivatives on TVFs, whose typical purpose is the assessment of the guarantee costs of such funds for insurers.     

共同基金和无风险资产投资的最优策略

利用均值-方差模型,分析了非线性交易成本下的共同基金与无风险资产投资组合的有效边界和在一般的效用函数下讨论了投资者的最优投资策略.     

Differential game approach to pricing and advertising decisions

This study proposes a model to make concurrent decisions on dynamic pricing and advertising to maximise firms' profitability over an infinite time horizon in a duopoly market. To this end, the Nerlove-Arrow pricing and advertising model is designed in the presence of shifting costs in a dynamic duopolistic competition as a differential game. The Nash equilibrium solution is defined based upon a set of Hamilton–Jacobi–Bellman. Four scenarios are applied for economic interpretations and the efficacy of the model.     

Worst-case portfolio optimization with proportional transaction costs

We study optimal asset allocation in a crash-threatened financial market with proportional transaction costs. The market is assumed to be either in a normal state, in which the risky asset follows a geometric Brownian motion, or in a crash state, in which the price of the risky asset can suddenly drop by a certain relative amount. We only assume the maximum number and the maximum relative size of the crashes to be given and do not make any assumptions about their distributions. For every investment strategy, we identify the worst-case scenario in the sense that the expected utility of terminal wealth is minimized. The objective is then to determine the investment strategy which yields the highest expected utility in its worst-case scenario. We solve the problem for utility functions with constant relative risk aversion using a stochastic control approach. We characterize the value function as the unique viscosity solution of a second-order nonlinear partial differential equation. The optimal strategies are characterized by time-dependent free boundaries which we compute numerically. The numerical examples suggest that it is not optimal to invest any wealth in the risky asset close to the investment horizon, while a long position in the risky asset is optimal if the remaining investment period is sufficiently large.     

Game options with gradual exercise and cancellation under proportional transaction costs

ABSTRACT

Game (Israeli) options in a multi-asset market model with proportional transaction costs are studied in the case when the buyer is allowed to exercise the option and the seller has the right to cancel the option gradually at a mixed (or randomized) stopping time, rather than instantly at an ordinary stopping time. Allowing gradual exercise and cancellation leads to increased flexibility in hedging, and hence tighter bounds on the option price as compared to the case of instantaneous exercise and cancellation. Algorithmic constructions for the bid and ask prices, and the associated superhedging strategies and optimal mixed stopping times for both exercise and cancellation are developed and illustrated. Probabilistic dual representations for bid and ask prices are also established.     

Replication and shortfall risk in a binomial model with transaction costs

The shortfall risk is defined as the optimal mean value of the terminal deficit produced by a self-financing portfolio whose initial value is smaller than what is required to replicate a contingent claim. In this paper we look for an explicit expression for it, as well as for the optimal strategy, when the market model is a binomial model with proportional transaction costs. We first study replication of European claims which satisfy suitable assumptions. We then investigate the shortfall minimization problem in a framework very similar to that without transaction costs. The author thanks the referee for useful comments on an earlier version of the present paper.