The Alpha Risk of Taguchi Method for LTB Type Quality Characteristic with L<Subscript>8</Subscript>

In Taguchi’s parameter design, the significant parameter levels are found by maximising the signal-to-noise ratio of the quality characteristic. In the analysis of variance (ANOVA) of signal-to-noise ratio, the combination of column effects to better estimate error variance is referred to as pooling. Taguchi has suggested the strategy of pooling up. When using the pooling-up strategy, there will be a tendency to make the alpha mistake more often. In this paper, it is assumed that (1) the quality chartacteristic is normally distributed and (2) the mean and standard deviation of each factor level combination are equal, then the null hypothesis should be no significant factor. Thus, the alpha risk is that some factors are misidentified as significant factors. The purpose of this paper is to investigate the alpha risk of the Taguchi method for the-larger-the-better (LTB) type problem with orthogonal array, L₈, by simulation. The results show that the alpha risk is very high.     

谈谈电力电容器保护技术

电力电容器组均压、稳压、降低线路系统损耗以及提高电力系统功率因数等方面有良好的表现性能,但同时又容易受到来自电流和电压等方面的损害,因而电力电容器的保护对于其自身功效和寿命的稳定乃至整个电力系统的正常运行有着十分重要的意义,本文就将从电流、电压、不平衡保护等方面对电力电容器保护技术进行分析。     

A CRITICAL REVIEW ON EVOLUTION OF RISK FACTORS AND FACTOR MODELS

The purpose of this work is to critically evaluate the evolution of risk factors and factor models. A systematic and structured literature review is carried out to observe and understand the past trends and extant patterns/themes in the present research area, evaluate contributions and summarize knowledge, thereby identifying limitations, implications and potential directions of further research. The main message from the study is that evolution of risk factors and factor models are continuous and endless development. Still today over 300 risk factors are identified by the researchers and many other yet to be discovered but out of them all only few are significantly responsible in explaining the stock markets risk return relationship. Study classifies risk factors into two groups: global and specific risk factors. Study answer the question ‘whether evolution of risk factors and factor models are endless development’. Finally, the present study gives an appropriate direction to the future studies to be taken in terms of risk factors and factor models. Due to continuous evolution and changing of nature of the risk factor it seems quite impossible to have a stable efficient factor models that can explain stock market risk return relationship globally in long run.     

Guidelines and an illustration of the use of ecological data for seeking clues of excess risk.

Ecological studies have acquired a bad reputation as weak scientific studies suffering from the ecological fallacy and many intractable limitations of data and method. In order to reduce these problems, it is suggested that analyses be focused on specific populations-at-risk, diseases, risk factors and places. In addition, seven guidelines are suggested which will limit the possibility of false positive results and provide the best clues for expensive, follow-up research. These guidelines are testing to make sure that the results are consistent across different times, places and methods. The guidelines were applied to finding the best clues for occupational-related cancers among white males aged 35-64 in the State of Illinois during 1950-1975. The most interesting clue found was that most coal mining areas in Illinois during the late 1960s and 1970s manifested the highest cancer mortality rates of trachea, bronchus, and lung and among the highest rates of increase of this type of cancer. This finding was unexpected because many studies have shown low lung cancer rates among coal miners.     

Realized jumps on financial markets and predicting credit spreads

This paper extends the jump detection method based on bipower variation to identify realized jumps on financial markets and to estimate parametrically the jump intensity, mean, and variance. Finite sample evidence suggests that the jump parameters can be accurately estimated and that the statistical inferences are reliable under the assumption that jumps are rare and large. Applications to equity market, treasury bond, and exchange rate data reveal important differences in jump frequencies and volatilities across asset classes over time. For investment grade bond spread indices, the estimated jump volatility has more forecasting power than interest rate factors and volatility factors including option-implied volatility, with control for systematic risk factors. The jump volatility risk factor seems to capture the low frequency movements in credit spreads and comoves countercyclically with the price–dividend ratio and corporate default rate.     

Optimal statistical decisions about some alternative financial models

We study Neyman–Pearson testing and Bayesian decision making based on observations of the price dynamics (_Xt:t∈[0,T])$(X_t:t\in [0,T])$ of a financial asset, when the hypothesis is the classical geometric Brownian motion with a given constant growth rate and the alternative is a different random diffusion process with a given, possibly price-dependent, growth rate. Examples of asset price observations are introduced and used throughout the paper to demonstrate the applicability of the theory. By a rigorous mathematical approach, we obtain exact formulae and bounds for the most common statistical characteristics of testing and decision making, such as the power of test (type II error probability), the Bayes factor and its moments (power divergences), and the Bayes risk or Bayes error. These bounds can be much more easily evaluated than the exact formulae themselves and, consequently, they are useful for practical applications. An important theoretical conclusion of this paper is that for the class of alternatives considered   neither the risk nor the errors converge to zero faster than exponentially in the observation time T$T$. We illustrate in concrete decision situations that the actual rate of convergence is well approximated by the bounds given in the paper.     

物流园区规划的风险问题及其防控

物流园区规划对物流园区建设和运营的成败有着十分重要的作用。物流园区规划过程包含诸多不确定因素,即风险。文章研究了物流园区规划风险识别的过程。按照物流园区规划的程序指出了物流园区规划过程中存在的风险因素,对其诱因进行了全面分析．并给出了物流园区规划风险的防控策略。     

Factor pricing of cryptocurrencies

In this paper, we study the cryptocurrency pricing factors. We review the literatures which state that the cryptocurrency market is weakly efficient. We use the Fama–MacBeth method to investigate the pricing factors. The classical equity-based risk factors including size, momentum, and value to growth from the Fama–French three factor model are studied. We use crypto-unique coin-to-token as a proxy for value-to-growth. For volatility risk factor category, we investigate realized volatility, skewness and jump. We also investigate liquidity factors including bid–ask, volume growth and Roll’s measure. The macro factors are found not to be an explanatory factor. The attention factor works sometimes. The factor model constructed by the significant factors explain most of the excess return of cryptocurrencies.     

Influence of equal or unequal comparison group sample sizes on the detection of differential item functioning using the Mantel–Haenszel and logistic regression techniques

In recent decades several methods have been developed for detecting differential item functioning (DIF), and many studies have aimed to identify both the conditions under which items may or may not be adequate and the factors which affect their power and Type I error. This paper describes a Monte Carlo experiment that was carried out in order to analyse the effect of reference group sample size, focal group sample size and the interaction of the two on the power and Type I error of the Mantel–Haenszel (MH) and Logistic regression (LR) procedures. The data were generated using a three-parameter logistic model, the design was fully-crossed factorial with 12 experimental conditions arising from the crossing of the two main factors, and the dependent variables were power and the rate of false positives calculated across 100 replications. The results enabled the significant factors to be identified and the two statistics to be compared. Practical recommendations are made regarding use of the procedures by psychologists interested in the development and analysis of psychological tests.     

Cross-sectional tests of asset pricing models with full-rank mimicking portfolios

In the standard tests of asset pricing models, factor risk premia are estimated on a test asset span so that models are tested with degrees of freedom reduced by the number of factors. Risk premia of traded factors can be further restricted to be equal to their expected returns, but such restrictions cannot be imposed on models with nontraded factors, which may create a problem of testing without full restrictions or on unequal asset spans across models. We propose a full-rank mimicking portfolio approach by projecting nontraded factors onto a combined span of test assets and benchmark traded factors. Under the Hansen-Jagannathan distance framework, we demonstrate that full-rank mimicking portfolios can provide improved power and fair performance comparison against a benchmark model in both specification and model comparison tests.     

Q‐FACTORS IN EMPIRICAL ASSET PRICING: A REVIEW AND SYNTHESIS

The latest development in the asset pricing literature is the emergence of empirical asset pricing models comprising q‐factors (profitability and investment factors) in conjunction with other factors. However, as in the case of the older empirical models, there is scepticism regarding the application of these newer factor models consisting of q‐factors because of the debate surrounding the explanatory power of these empirically inspired asset pricing models. This review attempts to synthesize studies pertaining to the four alternative explanations of the asset pricing models comprising the q‐factors (profitability and investment) – the data snooping hypothesis, the risk‐based explanation, the irrational investor behaviour explanation and the interpretation that suggest that the combination of the risk‐free asset and the factors comprising the model span the mean‐variance efficient tangency portfolio that prices the universe of assets.     

浅析海外电力工程项目风险的管理问题

由于国家宏观经济政策的调控导致了电力施工和建设系统竞争越来越激烈,工程建设也越来越困难。所以要想电力施工企业有良好的发展前途,就必须走出国门。海外建设项目的特点具有复杂性和面积大的影响性,所以在实施海外项目管理中存在非常大的风险,但风险也是可以避免的,只要通过分析各类风险并且对风险加以识别和分析,认真对待并且做好防范措施,那么海外项目的前景非常明朗并且能够在国际市场上占有一定的份额。     

Traditional beta, downside risk beta and market risk premiums

The article develops a downside risk asset-pricing model, which is based on Conditional-VaR (Mean-shortfall) risk measure. As in the traditional model the model leads to a monetary separation and yields a CVaR beta analogous to the traditional beta. An empirical study indicates that CVaR beta, which considers also downside risk, has greater explanatory power than the traditional beta. This is especially true in the case of a bearish market. Moreover, a combined model, which uses both betas, outperforms both the traditional and the CVaR models.The results indicate that in a bullish economy, risk premiums may be partially explained by the traditional beta. However, in a depressed economy investors are most likely more concerned about downside risk, which is poorly captured by the traditional beta. This downside risk can best be captured by CVaR beta, which is based on historical data and avoids assuming any prior distribution.     

Variance trading and market price of variance risk

This paper develops a new approach for variance trading. We show that the discretely-sampled realized variance can be robustly replicated under very general conditions, including when the price can jump. The replication strategy specifies the exact timing for rebalancing in the underlying. The deviations from the optimal schedule can lead to surprisingly large hedging errors. In the empirical application, we synthesize the prices of the variance contract on S&P 500 index over the period from 01/1990 to 12/2009. We find that the market variance risk is priced, its risk premium is negative and economically very large. The variance risk premium cannot be explained by the known risk factors and option returns.     

Monitoring risk in a ruin model perturbed by diffusion

We construct a nonparametric sequential test for the ruin probability and a corresponding change-point test in a risk model perturbed by diffusion. Some limiting properties are derived, which extend and improve on recent results of Conti (Stat Prob Lett 72:333–343, 2005) and Jahnke (Diploma thesis, University of Cologne, 2007). It is shown that the monitoring procedures can be designed such that the tests have an asymptotic prescribed false alarm rate (size) α and power 1. Some results from a small simulation study are also presented.     

BT模式下的市政工程投资风险分析

市政工程采用BT建设模式在我国应用越来越多。政府在一定时间内将市政工程项目全权交由投资承包商进行建设,政府对项目进行宏观控制、间接管理,因此投资控制难度很大,容易造成投资超支现象。因此采用BT模式,政府和投资承包商两个项目主体都面临相应的风险,在我国BT模式没有可参照的标准,项目涉及的参与方多,实施过程操作复杂,不确定性因素多的前提下,如何对项目进行投资控制,实现互利共赢,是需要解决的关键问题。本文根据市政工程BT模式的投融资特点,分析了市政工程BT项目的成本构成和费用控制的要点,梳理了市政工程BT项目回购基价影响因素,提出了控制回购基价的有效方式。并对BT模式下的市政工程风险进行了全面的分析。     

基础设施投资项目风险分析方法及管理

我国基础设施投资项目前期工作中，风险管理是一个十分薄弱的环节。在基础设施投资项目周期的全过程中，会出现各种不确定性因素，这些不确定性因素将对项目目标的实现产生积极或消极的影响。通过对项目风险的分析阐述。对可能造成的各种影响和影响程度进行定量的分析和评估。通过对不确定性因素的关注，对潜在风险的分析，对风险影响的揭示，采取相应的对策，从而达到降低风险的不利影响或减少其发生的可能性之目的。     

Forecasting economic activity from yield curve factors

This paper provides clear-cut evidence that the slope and curvature factors of the term structure of interest rates (yield curve) contain more information about future changes in economic activity than the term spread itself, often used in the literature as a predictive regressor of economic activity. These two factors reflect different information about future economic activity, which is smoothed out by the term spread. The paper shows that the slope factor has predictive power on future economic activity over longer horizons ahead, and thus may be interpreted as reflecting future business cycle conditions. On the other hand, the curvature factor, which enters the term spread with opposite sign than the slope factor, has predictive power on shorter movements of future economic activity which may be associated with changes in the current stance of monetary policy. These results hold for a number of world developed economies.     

基于灰色关联和回归分析的社会用电量预测研究

在电力市场化改革中,对社会用电量进行准确的预测十分必要。本文利用灰色关联分析理论对影响社会用电量的因素进行了筛选,再利用回归分析理论对社会用电量进行了预测。实例表明,灰色关联和回归分析理论应用于社会用电量预测是可行的。     

Robust design in multivariate systems using genetic algorithms

This paper presents a methodology based on genetic algorithms, which finds feasible and reasonably adequate solutions to problems of robust design in multivariate systems. We use a genetic algorithm to determine the appropriate control factor levels for simultaneously optimizing all of the responses of the system, considering the noise factors which affect it. The algorithm is guided by a desirability function which works with only one fitness function although the system may have many responses. We validated the methodology using data obtained from a real system and also from a process simulator, considering univariate and multivariate systems. In all cases, the methodology delivered feasible solutions, which accomplished the goals of robust design: obtain responses very close to the target values of each of them, and with minimum variability. Regarding the adjustment of the mean of each response to the target value, the algorithm performed very well. However, only in some of the multivariate cases, the algorithm was able to significantly reduce the variability of the responses.