A STATE-SPACE PARTITIONING METHOD FOR PRICING HIGH-DIMENSIONAL AMERICAN-STYLE OPTIONS

The pricing of American-style options by simulation-based methods is an important but difficult task primarily due to the feature of early exercise, particularly for high-dimensional derivatives. In this paper, a bundling method based on quasi-Monte Carlo sequences is proposed to price high-dimensional American-style options. The proposed method substantially extends Tilley's bundling algorithm to higher-dimensional situations. By using low-discrepancy points, this approach partitions the state space and forms bundles. A dynamic programming algorithm is then applied to the bundles to estimate the continuation value of an American-style option. A convergence proof of the algorithm is provided. A variety of examples with up to 15 dimensions are investigated numerically and the algorithm is able to produce computationally efficient results with good accuracy.     

Estimating demand with distance functions: Parameterization in the primal and dual

Our purpose is to investigate the ability of different parametric forms to ‘correctly’ estimate consumer demands based on distance functions using Monte Carlo methods. Our approach combines economic theory, econometrics and quadratic approximation. We begin by deriving parameterizations for transformed quadratic functions which are linear in parameters and characterized by either homogeneity or which satisfy the translation property. Homogeneity is typical of Shephard distance functions and expenditure functions, whereas translation is characteristic of benefit/shortage or directional distance functions. The functional forms which satisfy these conditions and include both first- and second-order terms are the translog and quadratic forms, respectively. We then derive a primal characterization which is homogeneous and parameterized as translog and a dual model which satisfies the translation property and is specified as quadratic. We assess functional form performance by focusing on empirical violations of the regularity conditions. Our analysis corroborates results from earlier Monte Carlo studies on the production side suggesting that the quadratic form more closely approximates the ‘true’ technology or in our context consumer preferences than the translog.     

信道估计偏差对空时编码的OFDM系统性能的影响

本文研究了采用空时编码的OFDM系统的性能，通过Monte Carlo仿真分析了系统性能和信道估计偏差对系统的影响。     

Testing for financial contagion based on a nonparametric measure of the cross‐market correlation

When contagion is defined as a significant increase in market comovement after a shock to one country, we propose a test for financial contagion based on a nonparametric measure of the cross-market correlation. Monte Carlo simulation studies show that our test has reasonable size and good power to detect financial contagion, and that Forbes and Rigobon's test (2002) is relatively conservative, indicating that their test tends not to find evidence of contagion when it does exist. Applying our test to investigate contagion from the 1997 East Asian crisis and the 2007 Subprime crisis, we find that there existed international financial contagion from the two financial crises.     

蒙特卡罗数值模拟法在随机参数转子动力学响应中的应用

本文运用模拟量输出卡和功率放大器生成符合正态分布的随机电流,根据已有的支撑刚度和随机电流之间的线性关系,得出支撑刚度的均值和标准差。在已有的转子系统模型上,利用蒙特卡罗数值模拟方法对随机参数进行模拟计算,得出支撑刚度参数的改变对转子动力学响应位移的影响。     

On the determination of an optimal sample size

Abstract

In works on sample survey theory and methods the sample size is usually regarded as determined by the sampling procedure and the total cost of the survey.     

MCMC ESTIMATION OF LÉVY JUMP MODELS USING STOCK AND OPTION PRICES

We examine the performances of several popular Lévy jump models and some of the most sophisticated affine jump‐diffusion models in capturing the joint dynamics of stock and option prices. We develop efficient Markov chain Monte Carlo methods for estimating parameters and latent volatility/jump variables of the Lévy jump models using stock and option prices. We show that models with infinite‐activity Lévy jumps in returns significantly outperform affine jump‐diffusion models with compound Poisson jumps in returns and volatility in capturing both the physical and risk‐neutral dynamics of the S&P 500 index. We also find that the variance gamma model of Madan, Carr, and Chang with stochastic volatility has the best performance among all the models we consider.     

A methodology for the choice of the best fitting continuous-time stochastic models of crude oil price

The crude oil price is generally considered as the fundamental factor in the valuation of undeveloped reserves but it is not the unique one. Undeveloped field value also depends on the uncertainty relating to the convenience yield and the risk-free interest rate. The purpose of this paper is to decide on the best continuous-time stochastic models for these risk factors. The Generalized Method of Moments and the Maximum Likelihood Estimation are implemented to fit the parameters of continuous-time stochastic processes. The results of unit root tests without breaks reveal a mean reversion in convenience yield series. Multiple structural change tests show that the risk-free interest rate can be considered constant. The simulation of continuous-time stochastic processes and the mean error between the simulated prices and the market ones show that the Geometric Brownian Motion with jumps is the best model for the oil price compared to the other commonly used processes.     

Forest transition in Northern Spain: Local responses on large-scale programmes of field-afforestation

Public field-afforestation schemes have been designed and widely implemented as a measure to alleviate uneven distribution, generate economic growth in rural areas and maintain or improve natural resources. The literature on forest management and planning has improved land-related information systems, allowing policy-makers to design and implement future policies on the allocation of forestland uses, and to forecast the land requirements of the target population more closely. The aim of this article is to empirically examine and validate the temporal and spatial land use changes and the socioeconomic effects linked to field-afforestation on private lands in the province of Lugo (Galicia, Northern Spain) at the municipal, parish and individual farm holding levels. Two main top-down field-afforestation programmes are reviewed in the study area: the national programme of public afforestations started with the implementation of Ley de Patrimonio Forestal del Estado (National Forest Estate Act; NFE) from 1941 to 2000, and the European aid scheme for forestry measures established under European Council Regulation No. 2080/1992 from 1993 to 1997. The results of a survey, targeted at 1355 farmers and conducted through questionnaires in the province of Lugo in 2004, complete the analysis of public intervention in forest management. The results indicate that the specific social, economic and environmental context of an agricultural and forestry area involves a differential heritage of land customs that determines a differential response model to forest programmes of land allocation and planning. Therefore, this must not be underestimated by the quantitative or qualitative general objectives of large-scale policies.     

中国风电产业技术创新对风电投资成本的影响

本文通过对学习曲线模型进行拓展,将规模效应对成本下降的影响从技术创新的影响中分离出来,解决了变量遗漏偏差的问题。并采用过程仿真方法,解决了中国风电时间序列数据样本过小的难题,提高了测算风电产业对新技术学习率的准确度。研究发现,中国风电产业的学习率仅为12.7%左右,即当风电累计装机容量增加2倍时,风电的单位投资成本因技术创新的下降率只有12.7%左右。由技术创新带来中国的成本下降不仅远远低于发达国家的,而且低于中国的太阳能等其他的新型可再生能源。因此政府在加大对风电基础科研投入的同时,应将政策的重点放在新技术的转化上。