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Constant conditional correlation in a bivariate GARCHmodel evidence from the stock markets of China_

Constant conditional correlation in a bivariate GARCHmodel evidence from the stock markets of China_
Constant conditional correlation in a bivariate GARCHmodel evidence from the stock markets of China_

Constant conditional correlation in a bivariate GARCH model:

evidence from the stock markets of China

Albert K.Tsui *,Qiao Yu

Department of Economics,National University of Singapore,Kent Ridge 119260,Singapore

Abstract

In this paper we examine the behaviour of stock returns in two emerging markets of China.These are the Shanghai and Shenzhen markets.It is found that both markets suffer from negative mean returns on Monday and Tuesday,but positive returns on Friday.In addition,we employ the bivariate GARCH model of Bollerslev [T.Bollerslev,Review of Economics and Statistics 72(1990)498±505]to capture the co-movements of stock returns between the markets.However,the information matrix test statistic does not support the null hypothesis of a constant conditional correlation in the stock returns.#1999IMACS/Elsevier Science B.V .All rights reserved.

Keywords:GARCH model;Stock returns;Shanghai and Shenzhen markets

1.Introduction

Modelling stock market volatilities by the generalized autoregressive conditional heteroscedasticity (GARCH)models has been an important research area in the last decade.Bera and Higgins [1]provide an excellent survey on the application of the GARCH models to the studies of many financial assets.The general consensus is that financial asset return volatilities have a predictable component which is dependent on the past volatilities and return shocks.As economic variables are often inter-related,and affected by the same set of available information,it is natural to extend the univariate GARCH models to multivariate GARCH models.Such generalizations would inevitably increase the number of parameters to be estimated and complicate specifications of the conditional variance and covariance matrix.Details are discussed in Engle and Kroner [2].

In an attempt to circumvent the tedious estimation and inference procedures,Bollerslev [3]introduced a bivariate GARCH model assuming constancy of the conditional correlation.However,the validity of the constant correlation assumption remains an empirical question.More recently,Bera and Kim [4]have derived a formal information matrix test for constancy of the conditional correlation,and applied it to well-developed stock markets in USA,Japan,Germany,UK,France and Italy.They found strong rejection of constancy of conditional correlation in all cases.In this paper,we examine the

Mathematics and Computers in Simulation 48(1999)

503±509

DDDD

*Corresponding author.

0378-4754/99/$20.00#1999IMACS/Elsevier Science B.V .All rights reserved.PII:S 0378-4754(99)00030-0

504 A.K.Tsui,Q.Yu/Mathematics and Computers in Simulation48(1999)503±509

constancy of conditional correlation in two emerging stock markets in China.They are the Shanghai and Shenzhen stock exchange markets.Given that these markets are relatively new and share similar sets of information,it would be interesting to see how the stock returns react with each other across markets.

The remainder of this paper is organised as follows.In Section2,we describe the methodology of the bivariate GARCH model.In Section3,we discuss the data used in this study.Section4reports the estimation and inference results.Section5provides some concluding remarks.

2.The bivariate GARCH model

Since the seminal work of Engle[5],the GARCH class of models has been instrumental in modelling time-varying volatility in financial time series.Bollerslev[3]extended the univariate GARCH model to bivariate GARCH models with time-varying conditional variance and covariance,but constant conditional correlation.Such a structure significantly simplifies the estimation and inference procedures.In this paper,we adopt the bivariate GARCH(1,1)model proposed by Bollerslev[3] with the following structure.

2.1.A simple mean-adjusted equation

Denote S it as the daily price index(i 1for the Shanghai market,and2for Shenzhen)and define r it 100?ln S it a S ità1 as the daily return on a continuously compounding basis.We assume that the mean equation of the return is captured by five dummy variables representing different expected returns for various days of the week.In addition,the residuals follow an autoregressive process of order q. Thus,the mean-adjusted equation can be written as:

5

"ij D tj u it(1) r it

j 1

q

ik u itàk it(2) u it

k 1

where r it is the return defined as the difference of the logarithmic prices,and D tj for j 1Y F F F Y5are the dummy variables with value1if the return is on the j th day of the week and value0otherwise.Hence, "ij represents the expected return of the j th day of the week.Also, ik are the respective autoregressive parameters.

2.2.Bivariate GARCH(1,1)model

We assume that under the null hypothesis the conditional correlation is constant over time so that all the variations over time in the conditional covariances are caused by changes in each of the corresponding two conditional variances.Let t 1t Y 2t H;then:

t jétà1$N O Y H t (3)

where ét à1is the '-algebra generated by all the available information up through time t à1and

H t h 1t h 12t

h 21t h 2t X (4)

Note that the conditional covariance matrix,H t ,is almost surely positive definite for all t ,and

h it i 0 i 1 2it à1 i h it à1Y i 1Y 2

(5)and

h 12t

& h 1t p

h 2t p X

(6)

The likelihood function of all unknown parameters 3is:

l t 3 à12log j H t j à12

1t 2t H à1t

1t 2t

X

(7)

The maximum likelihood estimation method is used to estimate all parameters of the bivariate

GARCH(1,1)model.2.3.The test statistic

To test the validity of the constant correlation assumption,Bollerslev [3]applied the Ljund±Box portmanteau test on the cross products of standardized residuals.However,serially uncorrelated cross product of residuals does not necessarily imply constancy of the conditional correlation over time.As such,we adopt the information matrix (IM)test formally derived by Bera and Kim [4]for the constancy of &.The test statistic is:

IM &

?N t 1 v ?21t v ?2

2t à1à2 &2 24N 1 4 &

2 &4 (8)

where

v ?1t ?1t à & ?2t

1à &2p (9) v ?2t

?2t à & ?1Y t

1à &

2p (10) & N t 1

?1t ?2t a N

(11)

and

?it

it a

h it p X (12)

Under the null hypothesis of constant correlation,IM &asymptotically follows a chi-squared

distribution with one degree of freedom.

A.K.Tsui,Q.Yu /Mathematics and Computers in Simulation 48(1999)503±509505

3.The data

We examine the conditional volatility of the Shanghai and Shenzhen stock markets of China.Shanghai is the most important industrial and financial centre in China,whereas Shenzhen is the pioneering market-oriented special economic zone.The Shanghai market commenced on 19December 1990,and the Shenzhen market started trading on 3April 1991.However,the Shanghai market set a daily price limit during the period of 19December 1990to 20May 1992.Initially,an upper and lower bound of 5%change of the share price was set,with subsequent adjustments.The price restriction was finally lifted on 21May 1992.As such,we disregard the observations within the period of price control.Our data set comprises 862daily price indices of the Shanghai and Shenzhen stock exchanges from 21May 1992to 13October 1995.All indices are price-weighted series of all listed stocks on the exchange.Table 1gives the summary statistics of the stock returns.It is noted that both the Shanghai and Shenzhen markets experience negative returns,with Shenzhen suffering from a greater average loss of 0.097%.Based on the magnitude of the unconditional standard deviations,the Shanghai market is more volatile.In addition,both markets generate very high kurtosis,and the kurtosis of the Shanghai market is more striking.

To examine the serial correlation in r t ,both in the mean and variance,we perform the nonparametric runs tests on r t ,|r t |,and r 2t ,respectively.The results in Table 1show that there is significant serial correlation in |r t |and r 2t ,but not in r t .We mention in passing that the correlation-integral statistic proposed by Brock et al.[6](denoted as BDS statistic)can be used to test whether a series is independently and identically distributed.If there is no deterministic chaotic structure in the data,the BDS statistic has an approximate normal distribution.4.Estimation and results

The estimation results of the mean-adjusted equations are summarised in Table 2.The model parameters are estimated using the maximum likelihood estimation method.The figures in parentheses are the standard errors.Both the Shanghai and Shenzhen markets exhibit significant serial correlation in their returns.Apparently,the order of the serial correlation is higher for the Shenzhen market.

In addition,the day-of-the-week effect (from Monday to Friday)is represented by the estimated values of "1,F F F ,"5.Both markets show negative mean returns on Monday and Tuesday,and positive return on Friday.However,not all of them are significantly different from zero at the 5%level.In

Table 1

Summary statistics of r it

Exchange

Mean S.D.Min.Max.Skewness Kurtosis I:Statistics

Shanghai à0.0683 4.1128à17.905128.8618373.694011.8308Shenzhen

à0.0970 3.3672à18.882828.2541

165.4875

14.9468

r t

|r t |r 2t II:Runs tests

Shanghai 2.1596à6.0175à8.0849Shenzhen

0.8435

à6.2411

à6.4727

506 A.K.Tsui,Q.Yu /Mathematics and Computers in Simulation 48(1999)503±509

particular,both markets have high and significant negative mean returns on the first trading day of the week.This is consistent with the observed negative returns on Monday in well-developed stock markets of USA,Canada,Singapore,and Hong Kong [7].Unlike the Shanghai market but like those in Japan and Australia,the Shenzhen market suffers from significant negative mean return on Tuesday.This matches with the observations reported by Jaffe and Westerfield [8].Moreover,the Shenzhen market also enjoys a high positive return on Friday (again like the US market).While acknowledging the fact that the day-of-the-week effect is rather unique to each stock market,the settlement procedure may explain part of the observed stock return pattern.

As the estimated parameters of the conditional mean and variance are asymptotically uncorrelated,we have performed the estimation by a two-step procedure.First,we estimated parameters of the mean equations of returns on the Exchanges in (1)and (2)using univariate autoregressive filters and dummy variables from OLS.The residual returns of the mean-adjusted equations were then employed to estimate parameters of the bivariate GARCH model in the second stage.The results are summarised in Table 3.As can be observed,all estimated coefficients for the variance equations are significant,thereby indicating the presence of GARCH effects.Table 4provides various diagnostic checks,including the nonparametric runs tests,Ljund±Box portmanteau tests [9],and the IM test.The

descriptive statistics m 3and m 4represent the usual sample estimates of skewness and kurtosis in the standardized residuals

it a h it p .Under the normality assumption,m 3and m 4should be 0and 3,respectively.However,excessive kurtosis and skewness are still present in the residual series.Such departures from normality are consistent with most of the empirical results on financial data.In addition,e t ,|e t |and e 2t represent the runs tests for the serial correlation in

it a h it p Y j it a

h it p j and

2it a h it ,respectively.Our results indicate a tremendous reduction in the serial correlation due to the conditional variance.The lack of serial correlation in the standardized residuals is more obvious for the

Table 2

Mean-adjusted equations

Exchange

"1"2"3"4"5I:Dummy variables

Shanghai à0.6650à0.44600.13010.18430.5072(0.3280)(0.3243)(0.3369)(0.3243)(0.3268)Shenzhen

à0.4639à0.3661à0.0113à0.00490.3325(0.0866)(0.0865)(0.0989)(0.0810)(0.0865) 1

2 3 4 5'

II:Model structure

Shanghai 0.03100.05070.03580.04470.038116.3614(0.0341)(0.0340)(0.0339)(0.0338)(0.0338)(0.7899)Shenzhen

0.01040.0447à0.05010.05750.035911.1772(0.0314)

(0.0320)

(0.0320)

(0.0319)

(0.0319)

(0.0902)

Table 3

Bivariate GARCH model Parameter 10 11 1 20 21 2&Estimates 1.79740.09690.5811 1.34420.08560.58530.4753Std.error

0.2592

0.0134

0.0487

0.1955

0.0140

0.0516

0.0175

A.K.Tsui,Q.Yu /Mathematics and Computers in Simulation 48(1999)503±509

507

Shanghai stock market.Moreover,results of the runs tests are consistent with those of the Ljund±Box test results recorded in Table 4.Here,Q 2(10)and Q 2(20)represent the Ljund±Box tests for up to the

10th and 20th order serial correlation in the squared standardized residuals, 2it a h it .They are all less than

the 5%critical values for both the Shanghai and Shenzhen markets.As such,we may conclude that the serial correlation caused by the conditional variance has been basically removed.

Under the null hypothesis of constant conditional correlation,the cross products of the standardized residuals should be serially uncorrelated.This is supported by the Ljund±Box tests which do not reject the hypothesis of no serial correlation.However,both the runs test and the information test formally derived by Bera and Kim [4]do not support the constant conditional correlation hypothesis.5.Concluding remarks

We have studied the behaviour of stock returns in the emerging Shanghai and Shenzhen stock exchange markets in China.We found that both markets suffer from negative mean returns on Monday and Tuesday,but enjoy a high positive return on Friday.This is consistent with most of the well-developed stock markets.In addition,we apply the information matrix test to detect the existence of constant conditional correlation in the two markets.However,our results do not support such a constancy.References

[1]A.K.Bera,M.L.Higgins,ARCH models:properties,estimation and testing,Journal of Economic Surveys 7(1993)305±

366.

[2]R.F.Engle,F.K.Kroner,Multivariate simultaneous generalized ARCH,Econometric Theory 11(1995)122±150.

[3]T.Bollerslev,Modelling the coherence in short-term nominal exchange rates:A multivariate generalized ARCH

approach,Review of Economics and Statistics 72(1990)498±505.

[4]A.K.Bera,S.W.Kim,Testing constancy of conditional correlation in bivariate GARCH model,Working paper,

Department of Economics,University of Illinois,1996.

Table 4

Specification tests

Exchange

m 3m 4e t |e t |e 2t I:Runs tests

Shanghai 5.75215.2260.893à1.932à1.659Shenzhen

6.70918.3100.613à2.815à2.642Q 2(10)

Q 2(20)Cross Q (10)Cross Q (20)Cross e t Cross |e t |II:Ljund±Box tests

Shanghai 2.160 5.119 2.721 4.207à3.037à2.906Shenzhen 3.986 5.620

2.721

4.207

à3.037

à2.906

IM &

III:IM test

Shanghai 612Shenzhen 612

508

A.K.Tsui,Q.Yu /Mathematics and Computers in Simulation 48(1999)503±509

A.K.Tsui,Q.Yu/Mathematics and Computers in Simulation48(1999)503±509509

[5]R.F.Engle,Autoregressive conditional heteroskedasticity with estimates of variance of United Kingdom Inflation,

Econometrica50(1982)987±1007.

[6]W.Brock,W.Dechert,J.Scheinkman,A test for independence based on the correlation dimension,Working paper,

University of Wisconsin at Madison,1987.

[7]K.A.Wong,T.K.Hui,Y.C.Choy,Day-of-the-week effects:evidence from developing stock markets,Applied Financial

Economics2(1992)49±56.

[8]J.Jaffe,R.Westerfield,The week-end effect in common stock returns:the international evidence,Journal of Finance40

(1985)433±454.

[9]G.M.Ljund,G.E.P.Box,On a measure of lack of fit in time series models,Biometrika65(1978)67±72.

七步洗手法操作考核评分标准

七步洗手法操作考核评分标准 项目 总分 评分细则分值评分标准得分 准备质量标准10分备齐用物(洗手液、一次性纸巾 或清洁毛巾) 5 漏一项扣1分。 衣帽整洁 5 衣帽不整齐扣1分,服装不 洁扣2分。 操作流程质量标准 70分1、洗手前修剪指甲,锉平甲缘, 清除指甲下的污垢。 5 双手指甲长度<1毫米(观察) 超过不得分。 2、打开水龙头,使双手充分淋湿。 5 使用方法不对全扣,污染一 处扣1分。 3、取适量洗手液,均匀涂抹至整 个手掌、手背、手指和指缝。 5 1、按七步洗手法的步骤。 2、认真揉搓双手15秒钟以 上,不足15秒扣10分。 3、要求每步均做,按顺序要 求。 4、少洗步骤,则扣除相应的 分值。 4、第一步:掌心相对,手指并拢, 相互搓擦。 5 第二步:手心对手背沿指缝相互搓 擦,交换进行。 5 第三步:掌心相对,双手交叉沿指 缝相互搓擦。 5 第四步:双手指相扣,互搓。 5 第五步:一手握另一手大拇指旋转 搓擦,交换进行。 5 第六步:将五个手指尖并拢放在另 一手掌心旋转搓擦,交换进行。 5 第七步:螺旋式擦洗手腕,交换进 行。 5 5、双手在流动水下彻底清洗。 5 6、关闭水龙头(用避免手部再污 染的方式)。 10 7、用一次性纸巾/小毛巾彻底擦 干。 5 终末质量 标准10分1、认真清洗指甲、指尖、指缝和 指关节等易污染部位,手部不佩带 饰物。 4 做不到不得分。 2、操作有序,每步方法正确,动 作连贯。 6 不熟练、不规范扣2分。 口述10分洗手指征10 知识点掌握50%以下不得分。洗手指征 a)直接接触每个患者前后,从同一患者身体的污染部位移动到清洁部位时。

英语语法专题条件状语从句(讲解+练习,无答案)

中考语法专题条件状语从句(讲解+练习,无答案)
条件状语从句
常用引导词:if, unless, as/so long as
1、if 从句 + 祈使句,“如果……,就……”
If you do not feel well, please go to see the doctor. 如果你感觉不舒服,就去看医生 吧。
If you want to know more about it, call now. 如果你想了解更多内容,现在就打电话 吧。
Make sure you visit the Science Museum if you ever go to London. 如果你去伦敦,一 定要去参观科学博物馆。
2、主将从现
If I start after dinner, I’ll finish it before I go to bed. 如果我晚饭后开始,睡觉前我就能 完成。
主句也可用“情态动词 + 动词原形” She may come with us if she arrives in time. 如果她来得及时,就可以和我们一起去。
3、if 条件状语从句和并列句的转换
Hurry up, or you’ll be late. = If you don’t hurry up, you’ll be late. Study hard and you will pass the exam. = If you study hard, you will pass the exam. 练习 (一)句型转换 1. Run fast, or you’ll be late for school. _______ you _______ _______ fast, you’ll be late for school. 2. You can buy the dictionary if you take enough money with you. Take enough money with you, _______ _______ _______ buy the dictionary. 3. If there is no air, none of us can live. None of us can live _______ _______.
4、unless “除非”
Don’t leave the building unless I tell you to. 不要离开大楼,除非我准许。 Unless you have finished your homework, I won’t allow you to watch TV. 除非你已完成 了作业,否则我是不会让你看电视的。 unless = if not You’ll be late if you don’t hurry. = You’ll be late unless you hurry. I can’t catch the train if I don’t get up early. = I can’t catch the train unless I get up early.
练习

if条件句中的虚拟语气讲解

虚拟语气(一) 一、考点聚焦 1、虚拟语气用于条件状语从句中 If I were a boy, I would join the army. If she had time, she should go with you. If h e had taken my advice, he would have succeeded in the competition. If i t were to rain tomorrow, the football match would be put off. If I had time, I would attend the meeting. If he had hurried ,he could have caught the train. If I were to go abroad ,I would go to America 如果我是你,我就会努力学习 If I were you, I would work harder at my lessons. 如果我知道他的电话号码,我就给他打电话了 If I had known his telephone number, I would have called him. 如果明天下雨的话,我们会取消比赛. If it should \were to rain, we would call off the match.

使用虚拟条件句要注意的几点: 1.当条件状语从句表示的行为和主句表示的行为所发生的时间不一致时,被称为:错综时间条件句“,动词的形式要根据它所表示的时间作出相应的调整. If you had followed my advice , you would be better now. 如果你听我的建议,你现在就会痊愈了. If you had studied hard before, you would be a college student now. 如果你努力学习的话,你现在就会是大学生了. If they had worked hard, they would be very tired now.(从句说的是过去,主句指的是现在) 2.省略句 在条件句中,可省略if,把were ,had, should 提到句首,变为倒装句式.If I were at school again, I would study harder. Were I at school again, I would study harder. If you had come earlier, you would have met him. Had you come earlier, you would have met him. If it should rain tomorrow, we would not go climbing. Should it rain tomorrow, we would not go climbing. Were I a boy, I would join the army. Had he taken my advice, he would have succeeded. Were it not for the expense, I would go to Britain. 2、虚拟语气用于名词性从句 (1)虚拟语气在宾语从句中的运用。 ①“wish + 宾语从句”表示不能实现的愿望,译为“要是……就好了”等。 表现在过去时 表过去过去完成时 表将来would, might, could+动词原形 I wish it were spring all the year round. I wish I had known the answer. I wish I could fly like a bird. I wish (that) I were a bird. I wish (that) I had seen the film last night. I wish (that) I would\could go.

条件句逻辑与汉语条件句的解释

条件句逻辑与汉语条件句的解释 条件命题 P → Q 前件:antecedent 后件:consequent 条件连词:→(箭头) →真值表 Conditional (where P is the antecedent and Q, the consequent; or P is the protasis and Q, the apodosis): P→Q 111 100 011 010 Modus Ponendo Ponens (MPP) 肯定前件律 A,A→B┝B Modus Tollendo Tollens (MTT) 否定后件律 ~B, A→B┝~A (1)P → Q (2)~Q → ~P (contraposition 质位互换)

充分条件同(1) 必要条件: (3)Q → P 对(3)作质位互换,得(4) (4)~P → ~Q (同(3)的必要条件关系) 举例: (5)So long as we scatter it, thought force is of little use to us, but as soon as we are prepared to take the trouble necessary to harness it, all knowledge is ours. (6)只要使用这种洗涤剂,便可洗得干干净净。 (7) 只要把球传给队友,他们就能得分。 (8) 只要你脸蛋长得还算过得去,哪怕一个字也不认识,也照样能当演 员。 以上充分条件句 (9)Nothing terrible will befall if you eat a piece of pizza — only if you exist on a diet of nothing but pizza. (10) We all agree that small stores are important, but they can remain viable only if they can carry out their trading on Sundays.

初中英语语法——If引导的条件状语从句(讲解及练习)

条件句从句主句 真实一般现在时一般将来时 情态动词+动原祈使句 非真实 一般过去时 be动词用(were) would/could+动原初中英语――条件状语从句(讲解&练习) Ⅰ条件状语从句的定义 Ⅱ条件状语从句的引导词 1.if引导的条件状语从句:表示在某种条件下某事很可能发生。 If we pay much attention to the earth, we'll have a better world. 如果我们多关爱地球,就会拥有一个更美好的世界 If it rains tomorrow, what shall we do? 如果明天下雨,我们怎么办? 注意:if还可以引导虚拟条件句,表示不可实现的条件,从句中多用一般过去时或过去完成时。 What would happen if there were no water ? 如果没有水会怎样? 2.unless引导的条件状语从句,unless的意思是如果不,除非。可与if...not互换。 You will fail in English unless you work hard. 你英语考试会不及格的,除非你更加努力。 3.as /so long as引导的条件状语从句:as /so long as意思是“只要” So long as you're happy,i will be happy. 只要你高兴,我就高兴。 Ⅲ条件状语从句的种类 Ⅳ条件状语从句的时态原则 用法例句 ①主句为一般将来时态,if从句用一般 现在时态(即主将从现)。We will stay at home if it rains tomorrow. 如果明天下雨,我将要呆在家。 ②主句中含有情态动词,if从句用一 般现在时态。If you finish your homework, you can go home now.如果你做完了作业,你现在可以回家了。 ③主句为祈使句,if从句用一般现在 时态。Don’t jump into the river if you feel very hot. 如果你感到很热,不要跳入河里。 ④主句为过去将来时,if从句用一般 过去时态(如果涉及到be动词, 一律都用were)。此时,表达的是和现实相反的推测,用虚拟语 气。If I were you, I wouldn’t do it like that.如果我是你,我就不会那么做的。 If you gave me some money, I would be very happy. 如果你给我一些钱,我就会很高兴的。 二、if 引导的条件状语从句 (1)“if 从句+祈使句”的句子。其实,if 作为一个连词,主句也可以是其他形式的句子。 例如:If you want to go, please let me know. (2)“祈使句 + and (or)+ 陈述句”

(完整版)七步洗手法操作考核评分标准

七步洗手法操作考核评分标准 姓名:科室:考核者:成绩: 项目总分评分细则分值评分标准得分备齐用物(洗手液、一次性纸巾、 3漏一项扣1分。 垃圾桶) 操作前质1、衣服整洁 量标准2、洗手前取下手表、首饰(手未污衣服装不洁扣0.5分,未5分染时)2取首饰扣0.5分,指甲长3、手无戴首饰度超过1毫米扣0.5分。 4、双手指甲长度<1毫米 2、1、暴露腕部 2、打开水龙头,使双手充分淋湿, 取适量洗手液,均匀涂抹掌面。 3、第一步:掌心相对,手指并拢, 相互搓擦。 4、第二步:手心对手背沿指缝相互 搓擦,交换进行。 5、第三步:掌心相对,双手交叉沿 操作中指缝相互搓擦。 质量标准6、第四步:双手指相扣,互搓。 70分7、第五步:一手握另一手大拇指旋 转搓擦,交换进行。

8、第六步:将五个手指尖并拢放在 另一手掌心旋转搓擦,交换进行。 9、第七步:螺旋式擦洗手腕,交换 进行。 10、双手在流动水下彻底清洗。 11、关闭水龙头(用手掌心接水冲洗 水龙头避免再污染手的方式)。 12、用一次性纸巾/小毛巾彻底擦干。 操作后质 量标准操作有序,每步方法正确,动作连贯。5分 口述20分洗手指征 合计2 2 8 8 8 8 8 8 8

3 2 5 5 20不熟练、不规范扣2分。 知识点掌握50%以下不得分。 1、按七步洗手法的步骤。 2、认真揉搓双手15秒钟以上,不足15秒扣10分。 3、要求每步均做,按顺序要求。 少洗步骤,则扣除相应的分值。 无暴露腕部扣2分使用方法不对每项扣0.5分。洗手与卫生手消毒应遵循原则 1、当手部有血液或其他体液等肉眼可见的污染时,应用肥皂液和流动水洗手; 2、手部没有肉眼可见污染时,宜使用速干手消毒剂消毒双手代替洗手。 洗手指征(六大指征) 两前:接触每个患者前、无菌操作前。 四后:接触每个患者后(检查患者身体污染部位移到清洁部位之间)、接触患者的血液、体液、分泌物、排泄物、伤口敷料等之后、穿脱隔离衣后或摘手套后、接触患者周围环境及物品后。 医务人员在下列情况时应先洗手,然后进行手卫生消毒1、接触患者的血液、体液和分泌物以及被传染性致病微生物污染的物品后; 2、直接为传染病患者进行检查、治疗、护理或处理传染患者污物之后。

if条件状语从句中虚拟语气

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指示条件句

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(完整版)if引导的条件句中的虚拟语气

if引导的条件句中的虚拟语气 虚拟语气表示一种不能实现的假设。该语法主要用于if条件状语从句。 一、if引导的条件状语从句的分类及虚拟条件句的判断 1、可以把条件句分为两类: 1).真实条件句(Sentences of Real Condition):凡是假设的情况发生性可能很大,就是真实条件句。例如: ⑴、If I have time , I will help you with this work.如果我有时间会帮助你做此工作的。 (2)、If time permits, we'll go fishing together.(如果有时间的话,我们就一起去钓鱼。) 2).虚拟条件句(Sentences of Unreal Condition):当假设是不大可能实现时,就是虚拟条件句。例如: ⑴、If I were you , I would have attended the meeting. 如果我是你的话,就去参加会议了。 ⑵、If he had come here yesterday, he would have seen his ol d friend.假如他昨天来这儿的话,就会看见他的老朋友。 ⑴、If it had rained yesterday, we would have stayed at home.(如果昨天下雨的话,我们就会留在家里。) 2、.if条件状语从句中虚拟语气的判断 判断是真实条件句还是非真实条件句。只有在非真实条件句中才使用虚拟语气。通过句子意思,看假设的条件是否能够实现,能

够实现是真实条件句,不能使用虚拟语气;假设的条件不能实现则是非真实条件句,要用虚拟语气。 判断这个假设是与哪个事实相反。通常有三种情况:①与过去事实相反。②与现在事实相反。③与将来事实可能相反。 3、“后退一步法” 后退一步法是指在准确地判断了该句与哪一事实相反后,按虚拟语气的后退一步法处理从句谓语动词的时态。即:在非真实条件状语从句中,谓语动词按正常情况“后退一步”。也就是: ①与过去事实相反,在从句中用过去完成时形式表示。 ②与现在事实相反,在从句中用过去一般时形式表示。 ③与将来事实可能相反,在从句中用过去将来时形式表示。 主句中则用情态动词would, should, could 等加一个与从句一致的动词形式。例: ⑴、If I had come her yesterday, I would have seen him. ⑵、If I were a teacher, I would be strict with my students. ⑶、If it should snow tomorrow, they couldn't go out. 4、注意事项 ①if条件句中如有were, should, had,可以省去if,并使用倒装语序。 ②在现代英语中if条件状与从句中的谓语动词如果是be其过去形式一般用were。

条件状语从句讲解(基础版本)演示教学

条件状语从句讲解 ――if引导的条件状语从句(注意&练习)在句子中做条件状语的从句称为条件状语从句。可置于句首、句尾,有时还可置于主语和谓语之间。引导条件状语从句的连接词有:if ,unless,as/so long as等 1.if引导的条件状语从句 表示在某种条件下某事很可能发生。 If we pay much attention to the earth, we'll have a better world. 如果我们多关爱地球,就会拥有一个更美好的世界 If it rains tomorrow, what shall we do? 如果明天下雨,我们怎么办? 注意:if还可以引导虚拟条件句,表示不可实现的条件,从句中多用一般过去时或过去完成时。What would happen if there were no water ? 如果没有水会怎样? 2.unless引导的条件状语从句 unless的意思是如果不,除非。可与if...not互换。 You will fail in English unless you work hard. 你英语考试会不及格的,除非你更加努力。 3.as /so long as引导的条件状语从句 as /so long as意思是“只要” So long as you're happy,i will be happy. 只要你高兴,我就高兴。 4.once引导的条件状语从句 once引导的条件状语从句,意为“一旦...,就”,从句可置于主句前或后 Once you begin,never stop. 一旦开始,就绝不要停止 Maths is easy to learn once you understand the rules. 一旦你理解了规则,数学就不难学了。

if引导的条件句中的虚拟语气

if引导的条件句中的虚拟语气?虚拟语气表示一种不能实现的 假设。该语法主要用于if条件状语从句。?一、if引导的条件状语从句的分类及虚拟条件句的判断 1、可以把条件句分为两类: 1).真实条件句(Sentences of Real Condition):凡是假设的情况发生性可能很大,就是真实条件句。例如:?⑴、If I have time, I will help youwith thiswork.如果我有时间会帮助你做此工作的。 (2)、Iftimepermits,we'll go fishing together. (如果有时间的话,我们就一起去钓鱼。) 2).虚拟条件句(Sentences of UnrealCondition):当假设是不大可能实现时,就是虚拟条件句。例如: ⑴、IfIwereyou ,I would have attended th e meeting.如果我是你的话,就去参加会议了。?⑵、I f he had come here yesterday, hewould have seen his oldfriend.假如他昨天来这儿的话,就会看见他的老朋友。?⑴、If ithadrained yesterday, we would have stayedathome.(如果昨天下雨的话,我们就会留在家里。)?2、.if条件状语从句中虚拟语气的判断?判断是真实条件句还是非真实条件句。只有在非真实条件句中才使用虚拟语气。通过句子意思,看假设的条件是否能够实现,能够实现是真实条件句,不能使用虚拟语气;假设的条件不能实现则是非真实条件句,要

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初中英语条件状语从句语法点和习题

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