Variance reduction for generalized likelihood ratio method by conditional Monte Carlo and randomized Quasi-Monte Carlo methods

The generalized likelihood ratio (GLR) method is a recently introduced gradient estimation method for handling discontinuities in a wide range of sample performances. We put the GLR methods from previous work into a single framework, simplify regularity conditions to justify the unbiasedness of GLR, and relax some of those conditions that are difficult to verify in practice. Moreover, we combine GLR with conditional Monte Carlo methods and randomized quasi-Monte Carlo methods to reduce the variance. Numerical experiments show that variance reduction could be significant in various applications.     

自相关检验方法的检验功效研究

研究目标:探究DW检验和LM检验的检验功效及其渐近性。研究方法:运用蒙特卡罗模拟实验方法结合相关影响因素对两种检验方法进行分析与比较。影响因素包括样本容量、解释变量的随机性及自相关性、随机误差项的自相关程度以及分布形态。研究发现:DW和LM检验功效与样本容量和随机误差项的自相关程度正相关,与解释变量的自相关程度负相关;解释变量的随机性对DW和LM检验功效无显著影响;误差项的几种常见分布形态的变化对DW和LM检验功效的影响可以忽略;在误差项存在一阶自相关的情况下,DW检验效果优于LM检验效果。研究创新:以DW检验和LM检验的假设条件为出发点,探究比较不同条件下自相关检验方法的检验功效。研究价值:在实证研究背景下为有效地选择自相关检验方法提供借鉴参考。     

一种简化的拟蒙特卡洛-高斯粒子滤波算法

提出了一种简化的拟蒙特卡洛-高斯粒子滤波（QMC-GPF）算法（SQMC-GPF）,以解决将QMC方法应用于GPF时计算复杂度高、运算量大的问题。该算法中，在连续的迭代滤波过程开始之前，首先利用QMC采样产生单位拟高斯分布粒子集，然后用其线性变换产生GPF算法中需要的高斯分布粒子集，省去了重新进行QMC采样步骤。该算法简化了新粒子集的产生过程，减少了运算量和滤波时间，增强了算法的实时性。将粒子滤波算法（PF）、GPF 算法、QMC-GPF算法和SQMC-GPF算法用于单变量非静态增长模型（UNGM）和二维纯角度跟踪模型（BOT）的仿真结果表明，SQMC-GPF算法的滤波性能与QMC-GPF算法的滤波性能相近，但有更为明显的速度优势，具有重要的实际应用价值。     

Robust inference in single firm/single event analyses

Single firm/single event (SFSE) studies are relevant in corporate finance. Since inference on abnormal returns in this context necessarily relies on the time series variance of these abnormal returns, the implied problem of heteroscedasticity is obvious, although hard to solve. We analyze robust inference in an SFSE setting using Monte Carlo and resampling experiments. Estimation is biased when the calibration and event period occur in different volatility regimes. We develop a unique specification test for these structural breaks. The most robust inference is obtained by using intraday data and a multiplicative component GARCH estimator.     

Study on the effect of sample size on type I error,in the first,second and first-two digits excessmad tests

The first-two digits ExcessMAD test was created in 2016, allowing to evaluate whether a certain data set conforms to Benford’s Law (BL). The purpose of this study is to explore some questions that remained open: develop the exact and approximate mathematical formulation of the first and second digit ExcessMAD test and study the type I error of these tests when applied to different sample sizes conforming to BL and to the uniform distribution, due to its wide use in accounting data. The importance of this study is to make available to accountants, auditors and researchers the first and second digit ExcessMAD tests, which will make it possible to conduct further investigations involving BL, especially for smaller samples. In addition, the relevance of the type I error analysis stems from the reduction of unnecessary additional studies for the investigation of non-conformity, in the case of the erroneous rejection of the null hypothesis stated as conforming to BL. The application of the second digit ExcessMAD test in the uniform distribution reveals that the close proximity between the uniform and BL distributions can lead to misinterpretations. Based on the exact and approximate mathematical formulations of the three ExcessMAD tests and the use of the Monte Carlo simulation technique, samples were generated in accordance with the BL and uniform distributions, with sizes between 100 and 3,500 elements, which allowed the study of type I error and the comparison of the tests applied to those distributions. This paper seeks to cover three gaps in the literature on ExcessMAD tests. In the previous studies, the following approaches were not found: the exact and approximate mathematical formulation of the first and second digit ExcessMAD tests; the analysis of type I error in these tests and the comparison of such results in the BL and Uniform distributions.     

低放固体废物处置场项目基本预备费估算研究 ——基于蒙特卡罗模拟法

目前我国对于核设施退役与放射性废物治理相关项目的需求日益增长,为确定现有规定中的各设计阶段的基本预备费费率是否能满足工程实际需求,本文针对低放固体废物处置场项目使用CRYSTAL BALL软件进行蒙特卡罗模拟,对工程的基本预备费进行计算。本文通过对两种方案分别进行Beta-PERT分布和正态分布模拟,得到不同置信区间下的基本预备费费用和费率并进行验证,得出基本预备费费率基本目前项目的实际情况,验证了蒙特卡罗模拟方法在低放固体废物处置场可行性研究阶段基本预备费的估算具有可行性,有良好的应用和推广价值。     

基于风险分析的缙云县耕地需求量预测研究

研究目的：从粮食安全角度，结合风险分析理念，进行耕地需求量预测，为制定政策提供依据。研究方法：运用蒙特卡罗模拟方法，以县域为例，分析人均粮食消费量、出生率、死亡率、粮食耕地单产、粮经比、复种指数、粮食自给率等因素的可能概率分布，对耕地需求量进行仿真预测。研究结果：得到具有一定可信度的耕地需求量风险区间值，其平均值与常规预测方法的结果接近，但比常规预测得到更多的信息。研究结论：通过风险分析得到的耕地需求量风险区间值比单一特定的值更具有政策意义，分析耕地需求量风险区间值，可协助分析相关政策措施的有效性，有利于土地利用规划的弹性管理。     

Cross-sector comovements and policy impact in the COVID-19 stock market: A dynamic factor approach

This study investigates the remarkable comovements in U.S. equity returns during the COVID-19 pandemic. It constructs a dynamic factor model (DFM) to illuminate the sources of the comovements and their implications. Using the Markov Chain Monte Carlo (MCMC) estimation method, the study finds that the comovements had a weak daily oscillation pattern during the pandemic. With that pattern, the study also finds significant monetary policy effects on the equity returns of several key sectors. In addition, it estimates the impact of news shocks, including monetary policy news, fiscal stimulus news, and unemployment news, on cross-sector equity returns. For any given sector, the conventional and unconventional monetary policy news shocked the sector in opposite directions. Among the positive monetary news shocks, the strongest were from interest rate policy surprises. Conversely, fiscal stimulus news had the most substantial positive impact and triggered all sectors to rebound from the bear market at the end of March 2020. Furthermore, by applying Natural Language Processing (NLP) sentiment analysis, this study sheds light on the positive correlation between comovements and news sentiment.     

高科技上市公司内在价值评估：基于连续型实物期权模型的实证研究

高科技企业高度不确定性的特征决定其本身具有潜在的期权价值,所以,传统的评估方法难以客观地评估出高科技公司内在价值.针对高科技公司高度不确定性的特征,引入Schwarz的连续型实物期权模型,在对模型进行离散化处理后,利用蒙特卡洛模拟对中国软件开发板块的高科技上市公司进行价值评估,并由此对整个软件开发板块的高科技上市公司价值评估进行的实证.研究发现,实物期权模型能较好地对高科技企业进行价值评估.     

BOT项目特许权期决策方法研究

特许经营期长短的决定是高速公路BOT特许权经营的一个核心问题。由于在特许经营期的确定直接关系到东道国政府和项目公司的利益分配,如果特许权期限较长,东道国的利益受损;特许权期限较短则会影响项目公司的利益,这都会导致BOT项目的失败。本文分析了一些影响特许权经营期的因素,并分析了这些因素对特许权经营期决策的影响,建立了基于蒙特卡罗方法来确定特许经营期的模型,从而提供了更系统的理论方法来判断和决策BOT项目特许经营期。