基于Copula的股票型开放式基金的组合风险度量

本文在＂推出股指期货和融资融券＂的新政策下,结合t-EGARCH模型和Copula方法对股票型开放式基金进行分析.该模型能更好地捕捉资产间的非线性相关性,更符合现实市场.并在此基础上,利用蒙特卡洛模拟计算了景顺增长基金前十大重仓股票及其投资组合的VaR值,从而验证了模型的有效性。     

基于CA模型的城市边缘区土地利用演变模拟——以广州市花都区为例

研究目的：探索土地利用的多地类CA模拟方法,并掌握城市边缘区土地利用变化规律。研究方法：选取典型城市边缘区 —— 广州市花都区为研究区域,利用C#语言结合ArcEngine GIS平台编程进行花都区土地利用演变CA模拟研究。以不同时间研究区土地利用图为基础数据,比较研究期内各地类的变化数量与方向以确定地类转换之间的优先级,并确定各地类的转换概率阈值。然后利用蒙特卡罗方法结合控制因素进行判断,最终确定元胞的转化状态。研究结果：模拟结果表明,2000 — 2005年间,新增建设用地分布在除北部山区以外的所有区域,但主要集中在城市中心区域,农用地主要分布在西南部和东北部,而且破碎化程度越来越高。在流向上,仍然有不少数量的农用地（主要为耕地和林地）转向建设用地。与实际情况相比,模拟的数量精度为84.8%,位置精度为71.3%。研究结论：研究结果表明此方法便于理解与操作,同时模拟精度较高。     

基于福州市降水量数据研究降水期权定价

为应对干旱、洪涝等降水事件给相关经济主体带来的风险,基于1953年1月至2016年12月福州市月均累积降水量数据,运用威尔克斯法对降水量进行建模,利用蒙特卡罗模法对降水期权进行定价从而得到降水期权价值,并提出发展我国降水期权的政策建议。     

Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies

This paper provides an investigation into the spillover effects of exchange rate returns and volatility for developed and emerging market currencies, using data from 1997 to 2011. The results suggest that spillovers in exchange rate returns have increased steadily over time, in moderate reaction to economic events. In contrast, spillovers in total observed volatility (measured by squared returns) react more strongly to economic events, and this transmission has remained at a relatively high level since the global financial crisis. Furthermore, over the course of time, global shocks would appear to account for a larger proportion of aggregate exchange rate volatility (and the relative importance of domestic shocks has declined). The paper also considers whether the increase in volatility spillover is due to sudden shocks, or whether it is due to changes in the stochastic trend of the underlying volatility process. The results suggests that in most cases, this increase is due to sudden shocks, however, in certain instances country‐specific events may perpetuate changes to the trend of the underlying volatility spillover.     

倒边盖挖逆作法基坑支护结构可靠性分析

为了解决采用标准Monte Carlo法计算复杂基坑工程上常见小概率失效,导致计算效率低的问题,以南京市湖南路地下商业街工程为工程背景,首先,将随机响应面法与基坑工程三维模型相结合,求解极限功能函数的响应面方程,并用标准Monte Carlo法计算失效概率和可靠指标,探讨采用倒边盖挖逆作法作为基坑支护结构施工方法的可行性;其次,基于该响应面方程,以土体的弹性模量为随机变量参数,采用马尔可夫链蒙特卡罗子集模拟法(MCMC子集模拟法)计算基坑支护结构的失效概率,并与标准Monte Carlo法结果进行对比分析。结果表明：当支护结构最大侧移控制指标为25 mm时,计算得到的可靠指标均大于4.6,即采用倒边盖挖逆作法施工过程中基坑是安全的;10万次和50万次标准Monte Carlo法计算得到的失效概率均为零,说明对于标准Monte Carlo法,在计算小概率失效问题时10万与50万的样本量是不足的;而MCMC子集模拟法用2.98万个样本计算出的结果与标准Monte Carlo法采用100万个样本计算的结果相对误差仅为1.7%,表明MCMC子集模拟法对于小概率失效问题求解的优势。所提算法在一定...     

Coverage area expansion, customer switching, and household profiles in the Japanese broadband access market

This paper examines the diffusion process of Internet broadband access in Japan by modeling the household choice of access modes. Estimates reveal that the characteristics of users, rather than those of the access modes, play a significant role in demand substitution across the modes. Simulation exercises indicate that had optic fibers (fiber-to-the-home; FTTH) been made available to the whole country in 2005, only 10% of households would have switched to that mode. This result implies that once chosen, the household choice of access mode persists, and that indirect network effects are an important element in decisions to adopt the new technology of broadband. Finally, policy implications are discussed.     

基于PCAIDS模型的单边价格效应模拟——以国际铁矿石巨头力拓与必和必拓拟议的兼并为例

本文基于爱泼斯坦和鲁宾菲尔德提出的PCAIDS 模型,模拟了国际铁矿石生产和出口巨头力拓与必和必拓之间2007 年10 月提出的兼并的单边效应.研究发现,该兼并对世界铁矿石市场价格将产生重要影响,特别是兼并后形成的新企业将大幅度提高其产品的价格.兼并也会引起印度、巴西和南非铁矿石提价,尽管幅度要比"两拓"要小一些.中国的进口铁矿石主要来自于两拓、巴西、印度和南非,因此,如果"两拓"兼并将极大地提高我国进口铁矿石的成本.     

Estimation employing a priori information within mass appraisal and hedonic pricing models

Both statistical appraisal and hedonic pricing models decompose houses into a set of individual characteristics. Regression estimates yield the contribution of each characteristic to total value. Unfortunately, straightforward application of OLS may produce untenable results such as implausible coefficient magnitudes or incorrect signs. Often the suspected cause is multicollinearity. This article examines the effect on estimation efficiency of differing levels of multicollinearity, R², and a priori information in the form of sub-market cost data, by comparing inequality restricted least squares (IRLS) with OLS in a series of Monte Carlo experiments. The IRLS procedure investigated here hybridizes the statistical market approach implemented by OLS, and the more traditional cost approach. The experiments show dramatic gains in estimation efficiency from exploiting a priori information through IRLS.     

Bias in estimates of discrimination and default in mortgage lending: The effects of simultaneity and self-selection

The common practices of estimating single-equation models of mortgage rejection to test for discrimination in mortgage markets or single-equation ex ante mortgage default equations to validate underwriting criteria produce biased and inconsistent parameter estimates. This is due to problems of simultaneous equations bias which arise because, in a world of imperfect information, mortgage terms are not exogenous to the rejection or default decision. In addition, mortgage default estimates are also subject to selection bias. Monte Carlo experiments are used to study the nature and extent of likely bias in single-equation estimation results. We find that rejection equation estimates indicate discrimination when none exists and that estimated coefficients of mortgage terms, such as the loan-to-value ratio, are also subject to significant bias in both rejection and default equations.     

MC's for MCMC'ists

We develop a minimum amount of theory of Markov chains at as low a level of abstraction as possible in order to prove two fundamental probability laws for standard Markov chain Monte Carlo algorithms:
1. The law of large numbers explains why the algorithm works: it states that the empirical means calculated from the samples converge towards their "true" expected values, viz. expectations with respect to the invariant distribution of the associated Markov chain (=the target distribution of the simulation).
2. The central limit theorem expresses the deviations of the empirical means from their expected values in terms of asymptotically normally distributed random variables. We also present a formula and an estimator for the associated variance.