The effects of tax reform on labor supply, tax revenue and welfare when tax avoidance matters

We examine how tax avoidance in the form of trade in well-functioning asset markets affects the study of labor supply. We discuss the implications for tax policy analysis, and we show that a failure to account for avoidance responses may lead to huge errors when analyzing how tax reform affects labor supply, tax revenue and the welfare cost of taxation. Our model may explain a number of otherwise hard to understand dimensions of taxpayer response.     

Multigeneration diffusion model for economic assessment of new technology

In the era of 21st century, development of emerging information technology is the essence of the advancement. This kind of new technology, however, often requires a great deal of amount of initial investment for both procedures of R&D and commercialization. As cost invested in developing the specified technology is increasing, investors are paying more attention to cost to benefit analysis (CBA). One of the basic elements of CBA for new technological development is the diffusion pattern of demand of such technology. Typically, it would be hard to presume the diffusion pattern of demand when the new product or the technology is under development. In this case, a simulation study is necessary. Many studies of technology evaluation have adopted a single generation model to simulate the diffusion pattern of demand. This approach, however, considers the diffusion of the new technology itself, not taking into account newer generation, which can replace the one just invented. In the real market situation, one must consider the competition and substitution phenomena between old and new technologies. In this paper, we show how multigeneration technology diffusion model can be applied for more accurate CBA for information technology. Additionally, Monte Carlo simulation is performed to find influential factors on the CBA of a cybernetic building system (CBS).     

A skeptical appraisal of the bootstrap approach in fund performance evaluation

It has become standard practice in the fund performance evaluation literature to use the bootstrap approach to distinguish “skills” from “luck”, while its reliability has not been subject to rigorous statistical analysis. This paper reviews and critiques the bootstrap schemes used in the literature, and provides a simulation analysis of the validity and reliability of the bootstrap approach by applying it to evaluating the performance of hypothetical funds under various assumptions. We argue that this approach can be misleading, regardless of using alpha estimates or their t‐statistics. While alternative bootstrap schemes can result in improvements, they are not foolproof either. The case can be worse if the benchmark model is misspecified. It is therefore only with caution that we can use the bootstrap approach to evaluate the performance of funds and we offer some suggestions for improving it.     

虚拟实验在电力拖动自动控制课程教学中的应用

把计算机仿真技术引入电力拖动自动控制系统课程的教学中 ,在计算机上进行虚拟实验 ,使抽象的教学形象直观 ,使学生掌握现代化的科学研究和工程设计方法 ,在提高教学质量 ,加强学生科学素养和能力培养中发挥了明显作用     

Valuation by Simulation of Contingent Claims with Multiple Early Exercise Opportunities

This paper introduces the application of Monte Carlo simulation technology to the valuation of securities that contain many (buying or selling) rights, but for which a limited number can be exercised per period, and penalties if a minimum quantity is not exercised before maturity. These securities combine the characteristics of American options, with the additional constraint that only a few rights can be exercised per period and therefore their price depends also on the number of living rights (i.e., American-Asian-style payoffs), and forward securities. These securities give flexibility-of-delivery options and are common in energy markets (e.g., take-or-pay or swing options) and as real options (e.g., the development of a mine). First, we derive a series of properties for the price and the optimal exercise frontier of these securities. Second, we price them by simulation, extending the Ibáñez and Zapatero (2004) method to this problem.     

A New Control Variate Estimator for an Asian Option

There exist several estimators for valuing the Asian option on the arithmetic mean. Among all variance reduction estimators, the one with the control variate derived from the geometric mean has been shown by Boyle et al. (1997) to perform best so far. In this paper, a new improved control variate estimator for this type of Asian option is proposed and investigated. Simulation results confirm that it does perform better than the control variate derived from the geometric mean. The improvement becomes more significant as the volatility increases and/or as the time to expiration lengthens.     

Learning competitive pricing strategies by multi-agent reinforcement learning

In electronic marketplaces automated and dynamic pricing is becoming increasingly popular. Agents that perform this task can improve themselves by learning from past observations, possibly using reinforcement learning techniques. Co-learning of several adaptive agents against each other may lead to unforeseen results and increasingly dynamic behavior of the market. In this article we shed some light on price developments arising from a simple price adaptation strategy. Furthermore, we examine several adaptive pricing strategies and their learning behavior in a co-learning scenario with different levels of competition. Q-learning manages to learn best-reply strategies well, but is expensive to train.     

Portfolio Value-at-Risk with Heavy-Tailed Risk Factors

This paper develops efficient methods for computing portfolio value-at-risk (VAR) when the underlying risk factors have a heavy-tailed distribution. In modeling heavy tails, we focus on multivariate t distributions and some extensions thereof. We develop two methods for VAR calculation that exploit a quadratic approximation to the portfolio loss, such as the delta-gamma approximation. In the first method, we derive the characteristic function of the quadratic approximation and then use numerical transform inversion to approximate the portfolio loss distribution. Because the quadratic approximation may not always yield accurate VAR estimates, we also develop a low variance Monte Carlo method. This method uses the quadratic approximation to guide the selection of an effective importance sampling distribution that samples risk factors so that large losses occur more often. Variance is further reduced by combining the importance sampling with stratified sampling. Numerical results on a variety of test portfolios indicate that large variance reductions are typically obtained. Both methods developed in this paper overcome difficulties associated with VAR calculation with heavy-tailed risk factors. The Monte Carlo method also extends to the problem of estimating the conditional excess, sometimes known as the conditional VAR.     

Linear rank tests for comparing treatments with a control when data are subject to unequal patterns of censorship

A class of asymptotically distribution-free tests is considered for comparing several treatments with a control when the, data are subject to unequal right-censorship. A particular member of this class is proposed for use in practice and an illustrative numerical example is given. A general result for the Pitman efficacy of a test based on an asymptotically normal test statistic is proved for the multiparameter case and using this result the efficacy of the proposed class of tests is obtained under sequences of translation and proportional hazards alternatives. Simulation studies are conducted to compare the performance of the proposed test, in terms of power, with some other tests.     

废弃钠钾合金起泡器搬运机器人自动上料装置设计

在非放射性废弃碱金属台架退役过程中,需将废弃的钠钾合金起泡器进行集中存储和处理,目前废弃碱金属容器多采用人工搬运,效率低且危险性较高.为解决碱金属氧化物容器安全搬运的难题,介绍一种专用搬运机器人自动上料装置的整体设计方案和设备布局,主要研究机械手末端执行器新型爪夹上料机构的设计和设备的电气控制系统,并对末端执行机构进行仿真分析.该装置不仅实现了搬运机器人上料的全自动化,而且大幅提高了效率,使得废弃钠钾合金起泡器搬运工作更加安全快捷.