Option hedging theory under transaction costs

The problem of option hedging in the presence of proportional transaction costs can be formulated as a singular stochastic control problem. Hodges and Neuberger [1989. Optimal replication of contingent claims under transactions costs. Review of Futures Markets 8, 222–239] introduced an approach that is based on maximization of the expected utility of terminal wealth. We develop a new algorithm to solve the corresponding singular stochastic control problem and introduce a new approach to option hedging which is closer in spirit to the pathwise replication of Black and Scholes [1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]. This new approach is based on minimization of a Black–Scholes-type measure of pathwise risk, defined in terms of a market delta, subject to an upper bound on the hedging cost. We provide an efficient backward induction algorithm for the problem of cost-constrained risk minimization, whose associated singular stochastic control problem is shown to be equivalent to an optimal stopping problem. This algorithm is then modified to solve the singular stochastic control problem associated with utility maximization, which cannot be reduced to an optimal stopping problem. We propose to choose an optimal parameter (risk-aversion coefficient or Lagrange multiplier) in either approach by minimizing the mean squared hedging error and demonstrate that with this “best” choice of the parameter, both approaches have similar performance. We also discuss the different notions of risk in both approaches and propose a volatility adjustment for the risk-minimization approach, which is analogous to that introduced by Zakamouline [2006. European option pricing and hedging with both fixed and proportional transaction costs. Journal of Economic Dynamics and Control 30, 1–25] for the utility maximization approach, thereby providing a unified treatment of both approaches.     

Economic dynamics of reservoir sedimentation management: Optimal control with singularly perturbed equations of motion

We analyze the economic dynamics of reservoir sedimentation management using the hydrosuction-dredging sediment-removal system. System dynamics depend on two interdependent hydraulic processes evolving at different rates. The accumulation of water impounded in the reservoir evolves on a ‘fast’ time scale, while the loss of water storage capacity to trapped sediments evolves on a ‘slow’ time scale. We formulate a multidimensional optimal control problem with singularly perturbed equations of motion to accommodate the disparate time scales. We apply singular perturbation methods to approximate (via polynomial series expansion) a ‘slow’ manifold reducing multi-dimensional solution space to the single-dimensional subspace confining long-term dynamics.     

Optimal pollution control with distributed delays

We present a model of optimal stock pollution control with general distributed delays in the stock accumulation dynamics. Using generic functional forms and a distribution structure covering a wide range of distributions, we solve analytically the complex dynamic system that arises from the introduction of these distributed delays. From a theoretical standpoint, our contribution extends the dynamic optimization literature that focused on single discrete delays and develops an original method to address control problems written as mixed type functional differential equations with general kernels. Our results show the qualitative impact of acknowledging these distributed delays on the optimal pollution paths dynamics. We study analytically the properties of the dynamics and we identify the conditions for the occurrence of limit cycles. This theoretical work contributes to the design of efficient environmental policies in the presence of complex delays.     

A network of options: Evaluating complex interdependent decisions under uncertainty

The present article provides a novel framework for analyzing option network problems, which is a general class of compound real option problems with an arbitrary combination of reversible and irreversible decisions. The present framework represents the interdependent structure of decisions by using a directed graph. In this framework, the option network problem is formulated as a singular stochastic control problem, whose optimality condition is then obtained as a dynamical system of generalized linear complementarity problems (GLCPs). This enables us to develop a systematic and efficient numerical method for evaluating the option value and the optimal decision policy.     

Dynamic advertising and pricing with constant demand elasticities

In this paper we analyze a stochastic dynamic advertising and pricing model with isoelastic demand. The state space is discrete, time is continuous and the planing horizon is allowed to be finite or infinite. A dynamic version of the Dorfman–Steiner identity will be derived. Explicit expressions of the optimal advertising and pricing policies, of the value function and of the optimal advertising expenditures will be given. The general results will be used to analyze the case of impatient customers. Furthermore, particular time inhomogeneous models and homogeneous ones with and without discounting will be examined. We will study the social efficiency of a monopolist's optimal policies and the consequences of specific subsidies. From a buyer's perspective, our analysis reveals that waiting – when looking at (immediate) expected prices – is never profitable should two or more units be available. But we will also prove that the sequence of average sales prices is monotone decreasing. Moreover, the techniques applied to solve the discrete stochastic advertising and pricing problem will be used to solve a related deterministic control problem with continuous state space.     

Rent control and complete contract equilibria

This paper develops a theoretical model for analysing the effects of rent control. The model incorporates the roles of optimal long-term contractual arrangements and the responses of individual agents to rent control in determining the economic characteristics of the controlled market equilibrium, and can help to explain the wide variation in empirical results observed across jurisdictions. Necessary and sufficient conditions for a complete contract equilibrium, where the characteristics of the competitive and controlled solutions are identical, are established. It is shown that housing quality, new construction, and the distribution of wealth may not be affected by rent control.     

Dynamic Modeling with Structural Equations and Stochastic Differential Equations: Applications with the German Socio-economic Panel

The paper discusses an application of linear dynamic models to multi-wave longitudinal data. Starting from three-wave and four-wave simplex models using standard structural equations, linear dynamic state space models with stochastic differential equations are presented. The main differences between longitudinal structural equations (static view) and stochastic differential equations (dynamic view) are emphasized. Substantively, the models prove the relation, stability and change of two concepts in a period of 10 years: National Identity and Intention to stay in Germany. Data from a sample of migrant workers in Germany included in the German Socio-economic Panel (GSOEP) are used for the analyses. Results and further developments of dynamic models are discussed in the final section.The authors thank Hermann Singer for his comments and discussions on applications of dynamic models.     

MODEL REFERENCE ADAPTIVE SYSTEM ESTIMATES FOR COUNTING PROCESSES

The adaptive estimation procedure of the model reference adaptive system is modified and applied to counting process models. Maximum likelihood estimates constitute a subclass of the adaptive estimators considered. The adaptive estimator is shown to be strongly consistent and to converge in law to a normal variate. Applications are considered; for example properties of the adaptive estimate are obtained for a periodic intensity model.     

R&D Outsourcing and the Effectiveness of Intangible Investments: Is Proprietary Core Knowledge Walking out of the Door?

Intangible relationship‐specific investments can be double‐edged swords, as they facilitate not only the governance of business relationships but also undesired knowledge transfers. Building on transaction costs theory and the relational view of alliances, we analyse the effectiveness of these investments in R&D outsourcing agreements from the viewpoint of the client. We argue that, when outsourcing to business firms, the safeguards adopted by the clients to prevent spillovers may reduce the effectiveness of the supplier's specialized investments. Using original survey data from 170 European and US technology‐intensive firms, we find that the contribution of these investments to client performance decreases the more a client's core knowledge is required to perform the service, except when outsourcing to non‐profits. This suggests that as the appropriability hazards associated with outsourcing to business firms rise, the client is able to capture less value from the supplier's relationship‐specific investments.