企业质量管理体系有效性评价研究

企业需要一种简便易行的质量管理体系有效性定量评价方法。本文从质量管理体系设计有效性和质量管理体系运行有效性两个方面提出了质量管理体系有效性评价指标体系,一级指标包括方针目标设计、过程设计、质量目标实现、产品质量、顾客满意和质量成本等方面。运用层次分析法设计了指标权重,提出了属性指标值的评分规则和计算方法。     

Optimal rules for ordering uncertain prospects

In this paper, we obtain the optimal selection rule for ordering uncertain prospects for all individuals with decreasing absolute risk averse utility functions. The optimal selection rule minimizes the admissible set of alternatives by discarding, from among a given set of alternatives, those that are inferior (for each utility function in the restricted class) to a member of the given set. We show that the Third Order Stochastic Dominance (TSD) rule is the optimal rule when comparing uncertain prospects with equal means. We also show that in the general case of unequal means, no known selection rule uses both necessary and sufficient conditions for dominance, and the TSD rule may be used to obtain a reasonable approximation to the smallest admissible set. The TSD rule is complex and we provide an efficient algorithm to obtain the TSD admissible set. For certain restrictive classes of the probability distributions (of returns on uncertain prospects) which cover most commonly used distributions in finance and economics, we obtain the optimal rule and show that it reduces to a simple form. We also study the relationship of the optimal selection rule to others previously advocated in the literature, including the more popular mean-variance rule as well as the semi-variance rule.     

CREDIT SCORING,STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE

Credit scoring has been regarded as a core appraisal tool of different institutions during the last few decades and has been widely investigated in different areas, such as finance and accounting. Different scoring techniques are being used in areas of classification and prediction, where statistical techniques have conventionally been used. Both sophisticated and traditional techniques, as well as performance evaluation criteria, are investigated in the literature. The principal aim of this paper, in general, is to carry out a comprehensive review of 214 articles/books/theses that involve credit scoring applications in various areas but in particular primarily in finance and banking. This paper also aims to investigate how credit scoring has developed in importance and to identify the key determinants in the construction of a scoring model, by means of a widespread review of different statistical techniques and performance evaluation criteria. Our review of literature revealed that there is no overall best statistical technique used in building scoring models and the best technique for all circumstances does not yet exist. Also, the applications of the scoring methodologies have been widely extended to include different areas, and this subsequently can help decision makers, particularly in banking, to predict their clients' behaviour. Finally, this paper also suggests a number of directions for future research. Copyright © 2011 John Wiley & Sons, Ltd.     

Properties of scoring auctions

This article studies scoring auctions, a procedure commonly used to buy differentiated products: suppliers submit offers on all dimensions of the good (price, level of nonmonetary attributes), and these are evaluated using a scoring rule. We provide a systematic analysis of equilibrium behavior in scoring auctions when suppliers' private information is multidimensional (characterization of equilibrium behavior and expected utility equivalence). In addition, we show that scoring auctions dominate several other commonly used procedures for buying differentiated products, including menu auctions, beauty contests, and price‐only auctions with minimum quality thresholds.     

Modelling small‐business credit scoring by using logistic regression,neural networks and decision trees

Previous research on credit scoring that used statistical and intelligent methods was mostly focused on commercial and consumer lending. The main purpose of this paper is to extract important features for credit scoring in small‐business lending on a dataset with specific transitional economic conditions using a relatively small dataset. To do this, we compare the accuracy of the best models extracted by different methodologies, such as logistic regression, neural networks (NNs), and CART decision trees. Four different NN algorithms are tested, including backpropagation, radial basis function network, probabilistic and learning vector quantization, by using the forward nonlinear variable selection strategy. Although the test of differences in proportion and McNemar's test do not show a statistically significant difference in the models tested, the probabilistic NN model produces the highest hit rate and the lowest type I error. According to the measures of association, the best NN model also shows the highest degree of association with the data, and it yields the lowest total relative cost of misclassification for all scenarios examined. The best model extracts a set of important features for small‐business credit scoring for the observed sample, emphasizing credit programme characteristics, as well as entrepreneur's personal and business characteristics as the most important ones. Copyright © 2005 John Wiley & Sons, Ltd.     

A Generalized Econometric Model and Tests of a Signalling Hypothesis with Two Discrete Signals

To test the major prediction of a signalling hypothesis-that the market price is monotonic in the signal-the price response to the signal must be measured. Since a signal is an outcome of a rational decision rule of the signaller, the market can infer the true type of the signaller from the signal. This necessitates estimation of the price response to the signal, conditional on the rational decision rule. Thus, the empirical models (e.g., event studies in corporate finance) that estimate the market price responses to signals without conditioning on the rational decision rules are misspecified if viewed as tests of the prediction of a signalling hypothesis. This paper builds a generalized econometric model with two possible discrete signals, derives the rational decision rules, presents a simple estimator of the price response to a signal, and illustrates its use in testing a recently expounded hypothesis that firms signal their true value by forcing or not forcing an outstanding convertible bond.     

Can central banks’ monetary policy be described by a linear (augmented) Taylor rule or by a nonlinear rule?

The original Taylor rule establishes a simple linear relation between the interest rate, inflation and the output gap. An important extension to this rule is the assumption of a forward-looking behaviour of central banks. Now they are assumed to target expected inflation and output gap instead of current values of these variables. Using a forward-looking monetary policy reaction function, this paper analyses whether central banks’ monetary policy can indeed be described by a linear Taylor rule or, instead, by a nonlinear rule. It also analyses whether that rule can be augmented with a financial conditions index containing information from some asset prices and financial variables. The results indicate that the monetary behaviour of the European Central Bank and Bank of England is best described by a nonlinear rule, but the behaviour of the Federal Reserve of the United States can be well described by a linear Taylor rule. Our evidence also suggests that only the European Central Bank is reacting to financial conditions.     

Nowcasting and the Taylor Rule

Actual federal funds rates in the U.S. have, at times, deviated from the recommendations of a simple Taylor rule. This paper proposes a “nowcasting” Taylor rule that preserves the form of the Taylor rule but encompasses realistic assumptions on information observable to policymakers. Because contemporaneous inflation rates and output gaps are not observable at the time policy is set, policymakers must form “nowcasts.” The optimal nowcast will depend, in part, on forecast uncertainty whenever policymakers have asymmetric costs to over‐ and underpredicting inflation and output. Empirical evidence shows that actual policy rates are consistent with those recommended by a nowcasting Taylor rule.     

Simple versus optimal rules as guides to policy

This paper compares the performance of different policy rules. Our comparisons focus on simple feedback rules versus rules which are optimal, given knowledge of the correct economic structure and the appropriate loss function for the policymaker. First, we compare rule performance when the correct model is not known. Second, we compare rule performance with respect to the frequency-specific behavior for variables of interest. Taken as a whole, our results indicate how the case for a model-specific optimal rule can break down when one relaxes the assumption that the true model is known as well as the assumption that the appropriate loss function is known. Links are made to the literature on monetary policy.     

开放条件下我国货币政策操作规则检验

本文利用我国1994—2006年的季度数据,分别对开放经济条件下的Taylor规则和McCallum规则进行了实证检验,结果表明,我国货币政策操作一直遵从McCallum规则,Taylor规则不适合我国国情。这意味着,如果经济结构不发生大的变化,就可以根据历史数据回归得到的McCallum规则的各种参数和通胀缺口、实际汇率、货币乘数、货币流通速度等变量的预期变化测算出合理的基础货币增长率,这将为调控基础货币供给提供重要参照。     

The accuracy of the tick test: Evidence from the Australian stock exchange

In the absence of information regarding whether a trade is buyer or seller initiated, many researchers have employed the ‘tick’ rule as a proxy. These researchers have been supported in their endeavours by the work of Lee and Ready (1991) which suggests that the tick rule is 90% accurate. Unfortunately, the difficulty of securing data on this issue has made Lee and Ready's paper somewhat unique in that there have been few attempts to confirm their result in US markets and no attempts in other markets. The purpose of this work is to test the robustness of their result in the Australian securities market. Using cleaner intra-day data we mimic the Lee and Ready study to cast some doubt upon the robustness of their findings in different markets. Our results suggest an overall accuracy of approximately 74% as opposed to Lee and Ready's 90%. However, accuracy in excess of 90% is documented when zero ticks are excluded. Further analysis provides evidence that a volatile or trending market will decrease the accuracy of the tick rule. It is also demonstrated that the tick rule is less likely to accurately classify seller initiated trades and small buyer initiated trades.     

A practical approach to validating a PD model

The capital adequacy framework Basel II aims to promote the adoption of stronger risk management practices by the banking industry. The implementation makes validation of credit risk models more important. Lenders therefore need a validation methodology to convince their supervisors that their credit scoring models are performing well. In this paper we take up the challenge to propose and implement a simple validation methodology that can be used by banks to validate their credit risk modelling exercise. We will contextualise the proposed methodology by applying it to a default model of mortgage loans of a commercial bank in the Netherlands.     

Rethinking priority: The dawn of the relative priority rule and the new “best interests of creditors” test in the European Union

This article identifies one aspect of the cross‐class cram‐down from the EU Directive on restructuring and insolvency that has not drawn wide attention to date. In addition to giving EU Member States the option of a “relative priority rule,” the European legislator has introduced a new “best interest of creditors” test, which does not—like in Chapter 11 of the US Bankruptcy Code—use the value that a party could expect in a hypothetical liquidation as a comparator but refers to the “next‐best‐alternative scenario.” First, this article addresses the concepts of the absolute and relative priority rule from the Directive and explores the motives for introducing the relative priority rule. In particular, a demand for more flexibility in restructuring negotiations, the call for an instrument to overcome structural hold‐out positions of preferential (priority) creditors in some Member States, as well as a trend in Europe to break with the “traditional laws of insolvency law” of law and economics seem to have inspired the legislator in drawing up the relative priority rule. This article then deals with the new “best interest” test and examines its interaction with the relative priority rule. It is shown that the concept of combining the new “best interest” test with the relative priority rule is coherent in theory. However, this article remains skeptical as to whether this interaction can succeed in practice, as the new “best interest” test is likely to add another stress point to the negotiations of restructuring plans.     

Quantifying and sustaining welfare gains from monetary commitment

Our objectives are: to quantify the stabilization welfare gains from commitment; to examine how commitment to an optimal rule can be sustained as an equilibrium; to find a simple interest rate rule that approximates the optimal commitment one. We utilize an empirical micro-founded euro-area DSGE model, a quadratic approximation of household utility as the welfare criterion, employing a nominal interest rate lower bound. In contrast to previous studies, we find significant commitment stabilization gains of around a 0.4-0.5% equivalent permanent consumption increase, and with higher price stickiness gains over 2%. We find that a simple optimized commitment rule responding to inflation and the real wage mimics the optimal one.     

Developing a Trading Rule from the FTSE-100 Stock Index Futures Contract: Evidence in Support of the EMH

An extensive literature documents the predictability of both short and long horizon returns, over a wide range of sample periods, frequencies and markets. This predictability may represent weak form inefficiency, or it may be caused by a failure to account for a time-variation in risk. We develop statistically reliable ex ante models of the returns on the FTSE-100 stock index futures contract and test a simple trading rule based on the out-of-sample predictions from these models. We interpret the failure of our ex ante model to produce abnormal returns for a risk neutral investor as evidence in favour of the EMH. Our trading rule results clearly suggest that we should be careful in interpreting such ex ante models as evidence of financial market inefficiency.     

Non-Linear Predictive Models for Intra-Day Foreign Exchange Trading

Artificial neural networks were used to search for non-linear relations in high- frequency foreign exchange time series. Three years (1985-7) tick-by-tick bid prices for the Swiss franc to the US dollar exchange rate were used in this study as training data to specify predictive models for intra-day trading, which was then tested on the same exchange rate time series in the following year (1988). A simple trading rule was adopted to evaluate the models, which showed statistically significant trading profit under moderate transaction costs. In contrast, a standard linear model did not produce profit with the same training and test data and under the same trading rule and transaction cost assumption. This provides evidence for the non-linear nature of the foreign exchange time series under study.     

Long-term optimal portfolios with floor

Long-term risk-sensitive portfolio optimization is studied with floor constraint. A simple rule to characterize its solution is mentioned under a general setting. Following this rule, optimal portfolios are constructed in several ways, using the optimal portfolio without floor constraint, combined with ideas of dynamic portfolio insurance, such as CPPI (constant proportion portfolio insurance), OBPI (option-based portfolio insurance), and DFP (dynamic fund protection). In addition, examples are presented with explicit computations of solutions.     

Time series momentum trading strategy and autocorrelation amplification

This paper investigates why general Moving Average (MA) trading rules are widely used by technical analysts and others. We assume general stationary processes for prices and we derive the autocorrelation function for an MA trading rule. Based on our results, we conjecture that autocorrelation amplification is one of the reasons why such trading rules are popular. Using simulated results, we show that the MA rule may be popular because it can identify price momentum and is a simple way of assessing and exploiting the price autocorrelation structure without necessarily knowing its precise structure. This paper then, provides empirical evidence of autocorrelation amplification using 15-year daily price data for 11 major international stock indices.     

Monetary Policy Response to Oil Price Shocks

How should monetary authorities react to an oil price shock? This paper shows that in a noncompetitive economy, policies that perfectly stabilize prices entail large welfare costs, hence explaining the reluctance of policymakers to enforce them. The policy trade‐off is nontrivial because oil (energy) is an input to both production and consumption. As welfare‐maximizing policies are hard to implement and communicate, I derive a simple interest rate rule that depends only on observables but mimics the optimal plan in all dimensions. The optimal rule is hard on core inflation but accommodates oil price changes.