VALUING A TIMBER HARVEST CONTRACT AS A HIGH‐DIMENSIONAL AMERICAN CALL OPTION VIA LEAST‐SQUARES MONTE CARLO SIMULATION

Abstract Industrial timberland ownership in the United States has shifted substantially in the last 20 years. Having sold their fee‐owned timberlands, forest products companies relied heavily on the open market for raw timber. To reduce their exposure to market risks, however, forest products companies have been using a number of supply chain instruments, such as timber harvest contracts. As these vehicles become increasingly important to the forest industry, it is necessary and important to determine their economic values. In this study, we treated a 3‐year timber harvest contract on a 30‐year‐old loblolly pine plantation as a high‐dimensional American call option and calculated its value by the least‐squares Monte Carlo simulation technique. The estimated values of such a contract ranged from $1,693/ac to $1,984/ac under two timber price assumptions. With reasonable starting timber prices and strike price in the simulation, random timber prices led to higher contract values. Results from this study can help private landowners, timber brokers, and forest products companies better manage their business risks.     

Spatial patterns of mortality in the United States: A spatial filtering approach

Within the field of spatial analysis, filtering has emerged as a powerful modelling technique to retrieve systematic patterns of geographical variation. In this work, spatial filtering is introduced in the context of modelling mortality for the first time in actuarial literature. Specifically, the objective of this research is to identify patterns in the spatial distribution of mortality rates for the sixty-five and older age group at the county level for the contiguous United States. The analysis carried out pertains to the spatial autocorrelation of these rates over time. The spatial filtering methodology is applied to uncover latent spatial patterns. Furthermore, the analysis reveals the extent to which these spatial patterns remained consistent across the years in the study. Results show the existence of spatial dependencies leading to an accompanying spatial filter. Thus, incorporating spatial filters as an exploratory tool in spatial analysis proves of considerable use when it comes to enriching traditional mortality models.     

The nature and extent of the geographic market for hogs in the United States

This paper looks at the question of whether hogs sold at different locations in the United States are part of a single geographic market covering the entire country. An answer to this question is sought using an approach to defining a geographic market based on the notion of instantaneous causality. The empirical results, based on prices for hogs at sixteen different locations over the period October 1989 to May 1992, suggest that there was but a single identifiable geographic market covering the entire United States. The implications of this finding are explored.     

TIMBER SUPPLY UNDER DEMAND UNCERTAINTY: WELFARE GAINS FROM PERFECT COMPETITION WITH RATIONAL EXPECTATIONS

ABSTRACT. This paper presents a noneconometric approach to estimating the short‐run timber supply function based on optimal harvest decisions. Determination of optimal harvest levels and estimation of supply function coefficients are integrated into one step by incorporating a parametric short‐run timber supply function into the harvest decision model. In this manner we convert the original harvest decision model into a new optimization problem with the supply function coefficients functioning as “decision variables.” Optimal solution to the new decision model gives the coefficients of the short‐run supply function and, indirectly, the optimal harvest levels. This approach enables us to develop stochastic models of the timber market that are particularly useful for forest sector analysis involving comparison of alternative institutional regimes or policy proposals and when the timber market is affected by stochastic variables. For demonstration purposes, we apply this method to compare the performances of two timber market regimes (perfect competition and monopoly) under demand uncertainty, using the Swedish data. The results show that the expected timber price is 22 percent lower and the expected annual timber supply is 43 percent higher in the competitive market than in the monopoly market. This confirms the theoretical result that monopoly reduces supply and increases price. The expected social welfare gain from perfect competition over monopoly is about 24 percent.     

On the modelling of nested risk-neutral stochastic processes with applications in insurance

We propose a modelling framework for risk-neutral stochastic processes nested in a real-world stochastic process. The framework is important for insurers that deal with the valuation of embedded options and in particular at future points in time. We make use of the class of State Space Hidden Markov models for modelling the joint behaviour of the parameters of a risk-neutral model and the dynamics of option market instruments. This modelling concept enables us to perform non-linear estimation, forecasting and robust calibration. The proposed method is applied to the Heston model for which we find highly satisfactory results. We use the estimated Heston model to compute the required capital of an insurance company under Solvency II and we find large differences compared to a basic calibration method.     

TIMBER MARKETS AND FUEL TREATMENTS IN THE WESTERN U.S.

ABSTRACT. We developed a model of interrelated timber markets in the U.S. West to assess the impacts of large‐scale fuel reduction programs on these markets, and concomitant effects ofthe market on the fuel reduction programs. The linear programming spatial equilibrium model allows interstate and international trade with western Canada and the rest of the world, while accounting for price effects of introducing softwood logs to the market. The model maximizes area treated, given fire regime‐condition class priorities, maximum increases in softwood processing capacity, maximum rates of annual treatments, prohibitions on exports of U.S. and Canadian softwood logs from public lands and a fixed annual treatment budget. Results show that the loss to U.S. private timber producers is less than the gains for timber consumers (mills). States receiving more treatments when spending is not constrained by state proportions include Idaho, Montana, New Mexico and Oregon. When only the wildland‐urban interface is treated, California, Oregon and Washington receive more treatments. Utah and Colorado receive more treatments when low risk stands are included.     

侦测股市时间序列相关性的三种方法

运用方差方法.重标极差方法(R/S)和消除趋势波动分析方法(DFA)对美国股市标准普尔500指数的收盘价进行分析.结果表明:此股票市场指数具有状态持续性特征及自相似特征.同时兼具混沌等非线性特征.通过这三种方法对同一股市进行分析更能全方位的诠释相关性在股票市场理论应用的必要性及可行性,并且对股票市场理论建模.预测和管控策略的制定及实施具有重要意义.     

Factors affecting the demand for softwood lumber in the united states

This study sets out to examine whether the demand for softwood lumber in the United States is responsive to various market factors including the price of softwood lumber, the price of other building materials, and the level of economic activity (e.g. housing starts). Concern in the analysis is focused on overcoming some of the methodological shortcomings found in previous studies of this issue. The results are conclusive. The quantity of softwood lumber demanded does respond to the various economic factors considered. Moreover, when the structural stability of the estimated relationships is investigated, the results suggest that the demand for softwood lumber regionally in the United States has remained unaltered over the sample period (1950–1985).     

Practical convergence conditions for the Davidon-Fletcher-Powell method

The convergence properties of the Davidon-Fletcher-Powell method when applied to the minimization of convex functions are considered for the case where the one-dimensional minimization required at each iteration is not solved exactly. Conditions on the error incurred at each iteration are given which are sufficient for the original method to have a linear or superlinear rate of convergence, and for the restarted version to have ann-step quadratic rate of convergence.Sponsored by the United States Army under Contract No. DA-31-124-ARO-D-462.     

资产价格中跳的检验与度量

分离估计归因于跳部分和连续部分对资产定价是非常重要的.由于市场信息的流入,前者通常比后者缺少可预测性.到目前为此,小波方法对于发现跳点和估计跳大小是有力的,正如王亚珍[1].但是在一些程度上,在点估计方面不能准确地对跳的位置和大小进行估计.本文中,我们提出了改进方法去估计已实现方差,从而新的估计量被用于在不同的取样策略...     

A system dynamics model for long range planning in railroad

The model represents dynamic interactions between railroad track and equipment management, freight market share and internal financial variables. The model was applied to Consolidated Rail Corporation (Contrail) in the United States to evaluate impacts of different policies on Conrail's performance. In the base simulation run, Conrail slowly deteriorates physically and financially from 1980 to 2000. Simulation results indicate that only a few policies — like track abandonment and increased productivity — can cause permanent improvement in the railroad's physical and financial condition.     

On the approximation of empirical data for service system simulations

The difficulties associated with parameter estimation for phase-type approximations of empirical data distributions in queue modelling are well known. While significant progress has been achieved in improving such approximations, difficulties in parameter estimation still limit the extent to which queue modelling is applied in practice. This paper presents a simplified technique for approximating empirical data in service system simulations, based on the specialised Cox phase-type distribution. When utilised in simulation modelling of a service system, the specialised Cox distribution is shown to provide improved approximations to the combined waiting and service time distribution without the need for complex parameter estimation techniques. This approach should enable much greater flexibility in the application of queue modelling to service systems.     

An assessment of interfuel substitution by electric utilities

This paper applies a translog model to a pooled sample in order to measure the extent of regional interfuel substitution effects in the electric power industry. The results obtained indicate that relative changes in fuel prices both regionally and nationally have significant effects on fossil fuel consumption. This, in turn, has important implications for public policy. In particular, the market system appears better able to deal with exogenous shifts in energy supplies than has frequently been assumed in the formulation of public policies toward the energy crisis.Further, compared to aggregate United States time series estimates, a more elastic fuel price response is found thus questioning whether full long-run adjustment is being measured in the pure time series estimates. Given the importance of the latter in energy tax policy analysis for example, the question is indeed more than academic.     

Evolutionary computation of a deterministic switching regressions estimator

Summary  A deterministic switching regressions estimator is evaluated using an evolutionary method based on genetic algorithms. Distinctive aspects of the method include (1) a combination of simple and random chromosomal crossover and (2) extension of the principle of natural selection to internal parameterization. The evolutionary computation duplicates, significantly faster, the results of an existing enumerative method in samples small enough to permit enumeration. It also provides the ability to calculate the estimator in much larger sample sizes than is possible with the enumerative approach. An example problem from the United States gasoline market is given. Funding support provided by the Gerondelis Foundation, Inc. is gratefully acknowledged.     

Fuzzy linear regression and its applications to forecasting in uncertain environment

Linear regression has been used for many years in developing mathematical models for application in marketing, management, and sales forecasting. In this paper, two different sales forecasting techniques are discussed. The first technique involves non-fuzzy abstract methods of linear regression and econometrics. A study of the international market sales of cameras, done in 1968 by John Scott Armstrong, utilized these non-fuzzy forecasting techniques. The second sales forecasting technique uses fuzzy linear regression introduced by H. Tanaka, S. Uejima, and K. Asai, in 1980. In this paper, a study of the computer and peripheral equipment sales in the United States is discussed using fuzzy linear regression. Moreover, fuzzy linear regression is applied to forecasting in an uncertain environment. Finally, some possible improvements and suggestions for further study are mentioned.     

A hybrid data mining/simulation approach for modelling outpatient no-shows in clinic scheduling

This paper considers the outpatient no-show problem faced by a rural free clinic located in the south-eastern United States. Using data mining and simulation techniques, we develop sequencing schemes for patients, in order to optimize a combination of performance measures used at the clinic. We utilize association rule mining (ARM) to build a model for predicting patient no-shows; and then use a set covering optimization method to derive three manageable sets of rules for patient sequencing. Simulation is used to determine the optimal number of patients and to evaluate the models. The ARM technique presented here results in significant improvements over models that do not employ rules, supporting the conjecture that, when dealing with noisy data such as in an outpatient clinic, extracting partial patterns, as is done by ARM, can be of significant value for simulation modelling.     

基于遗传算法的木材物流中心选址研究

分析了木材物流模式,建立物流中心选址的数学模型,研究遗传算法求解选址模型的方法,并以永安林业集团股份有限公司的木材物流数据为基础,提出研究区域内木材物流中心选址的实际模型,采用可重复自然数编码的遗传算法求解模型,运用VB编写相应的程序,提高选址决策的效率和精度。     

Notes on spline functions IV: A cardinal spline analogue of the theorem of the brothers Markov

A cardinal spline analog of the Markov theorem is given. It is applied to derive the necessary conditions for a function to be the limit of its cardinal spline interpolents as their degree trends to infinity. Sufficient conditions for this to happen are given in [8]. Sponsored by the United States Army under Contract No. DA-31-124-ARO-D-462.     

Bootstrapped confidence bands for percentile lifetime

Summary We propose bootstrapped confidence bands for the percentile lifetime function. Our method is based on a joint approximation of the empirical and quantile processes and their bootstrapped counterparts. Modest simulations support the results. Confidence bands are applied to quantile and median residual lifetimes of tractor rear brakes. Research done while at Carleton University Norman Paterson Centre: also partially supported by NSERC Canada grants of M. Cs?rgő. Research supported in part by a NSERC Canada operating grant. Research done while at Carleton University; also partially supported by NSERC Canada grants of m. Cs?rgő and D. A. Dawson and by an EMR Canada grant of M. Cs?gő. Research supported in part by a United States Department of Agriculture CSRS grant and a United States NSF grant of D. M. Bates, G. Wahba and B. S. Yandell.     

Large-scale controlled rounding using tabu search with strategic oscillation

When publishing tabular data, the United States Bureau of the Census must sometimes round fractional data to integer values or round integer data to multiples of a prespecified base. Data integrity can be maintained by rounding tabular data subject to additivity constraints while minimizing the overall perturbation of the data. In this paper, we describe a heuristic based on tabu search with strategic oscillation for solving this NP-hard problem. A lower-bounding technique is developed in order to evaluate the quality of the solutions and provide a starting solution for the tabu search. Numerical results demonstrate the effectiveness of the procedure when applied to extremely large tables with up to 27,000 randomly generated entries. Additionally, the algorithm is shown to perform extremely well when applied to actual data obtained from the United States Bureau of the Census.