Housewives of Tokyo versus the gnomes of Zurich_ Measuring price discovery in sequential markets

Housewives of Tokyo versus the gnomes of Zurich_ Measuring price discovery in sequential markets
Housewives of Tokyo versus the gnomes of Zurich_ Measuring price discovery in sequential markets

Journal of Financial Markets 14(2011)82–108

Housewives of Tokyo versus the gnomes of Zurich:Measuring price discovery in sequential markets $

Jianxin Wang n ,Minxian Yang

Australian School of Business,University of New South Wales,Sydney 2052,Australia

Available online 7August 2010

Abstract

This paper presents two methods to measure market-speci?c contributions to price discovery in non-overlapping sequential markets:one is a non-parametric approach using high-frequency data and the other is a structural VAR model based on open-to-close returns.The methods complement the existing methodologies for comparing price discovery in parallel https://www.360docs.net/doc/ad17183169.html,ing these methods,we estimate the information shares of four sequential markets for the trading of AUD,JPY,EUR,and GBP against USD over an eight-year period.We ?nd that price discovery in the foreign exchange markets are still dominated by Europe and the United States,particularly the London–New York overlapping trading https://www.360docs.net/doc/ad17183169.html, is losing information shares to Europe in the trading of AUD and JPY.The signi?cance of the ‘‘housewives of Tokyo’’in currency trading may have been overstated.

Crown Copyright &2010Published by Elsevier B.V.All rights reserved.

JEL classi?cation:G14;G15;C32

Keywords:Price discovery;Information share;Sequential markets;Realized variance;Beverage-Nelson decomposition;Ef?cient price;Foreign exchange rate

‘‘Years ago,it was the gnomes of Zurich who shook the foreign exchange markets.They have now been replaced by the housewives of Tokyo,who speculate in various

https://www.360docs.net/doc/ad17183169.html,/locate/?nmar

1386-4181/$-see front matter Crown Copyright &2010Published by Elsevier B.V.All rights reserved.doi:10.1016/j.?nmar.2010.08.002

$

We appreciate helpful comments from Douglas Foster,Frederick Harris,Joel Hasbrouck,Bruce Lehmann,Ron Masulis,S.Ghon Rhee,Maxwell Stevenson,Shuji Watanabe,and participants at seminars at the University of New South Wales,Monash University,Xiamen University,the microstructure conference at the University of Sydney,and the 2009FMA Asian Conference.We thank the Securities Industry Research Centre of Asia-Paci?c (SIRCA)for providing the foreign exchange data.n

Corresponding author.Tel.:t61293855863;fax:t61293856347.

E-mail addresses:jx.wang@https://www.360docs.net/doc/ad17183169.html,.au (J.Wang),m.yang@https://www.360docs.net/doc/ad17183169.html,.au (M.Yang).

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10883 currencies.However,whereas the gnomes of Zurich were accused in their day of destabilizing markets,the housewives of Tokyo are apparently acting to stabilize them.Their presence seems to lie behind the marked decline in(perceived)volatility in yen-dollar exchange rates.y The housewives are betting against professional investors in the IMM,1and seem to be pro?ting from their trading so far.’’

Dr.Kiyohiko Nishimura,Bank of Japan.2

1.Introduction

The above speech,given at the Brookings Institution in Washington on July2,2007, created the metaphorical‘‘Mrs.Watanabe,’’whose currency trading and market impact captured the imagination of?nancial press.‘‘Now,a new beast is roiling markets—Mrs. Watanabe,or Japan’s archetypal housewife,’’says the Financial Times on the next day.‘‘On her shoulders may lie responsibility for some of the stability of the global?nancial system,’’according to The Economist(August16,2007).The speech by Dr.Nishimura, along with the press commentaries,suggests that retail investors in Japan have signi?cant market impact in currency trading.However,Tokyo is not a leading hub for currency trading,not even for yen-related transactions.3Its share of currency trading has been declining relative to markets elsewhere.If indeed the‘‘housewives of Tokyo’’are replacing the‘‘gnomes of Zurich’’and winning against futures traders in Chicago,it would suggest that trading in Tokyo has greater price impact than trading in Europe and North America. Is Tokyo a leading information hub for currency trading,particularly for the yen?How does one measure the signi?cance of Tokyo trading to the pricing of the Japanese yen relative to trading in markets in Europe and North America?

This paper aims to address these questions.It proposes and compares two approaches to estimate the contribution of a particular market to the price discovery of an asset traded in multiple markets.The global?nancial liberalization has resulted in more assets than ever before being traded in multiple markets around the world.As companies and economies become more exposed to global risk factors,knowing where price discovery occurs often sheds light on what factors affect asset prices.A cross-market comparison of price discovery provides an estimate of the distribution of information and information-based trading for the underlying asset.A market’s contribution to price discovery re?ects its ef?ciency in collecting and analyzing information,the quality of its regulation and microstructure,as well as its liquidity,which are important for attracting informed investors.With changes in global economic conditions and trading technology,the signi?cance of a market may change over time.The traditional link between an asset,e.g., the Australian dollar and a particular market,e.g.,Sydney,may be weakening.While of?cials in Japan are concerned with maintaining the global status of the Japanese?nancial markets,markets in Shanghai are getting greater global attention.Understanding what 1IMM stands for the International Monetary Market of the Chicago Mercantile Exchange,a major venue for the trading of currency futures.

2Dr.Nishimura is currently the Deputy Governor,Bank of Japan.His speech is published as Nishimura(2007). 3The BIS survey shows that U.K.and U.S.account for34%and16.6%of global currency transactions respectively.Japan’s share of currency trading has declined from9.1%in2001to6%in2007and is similar to that of Switzerland(6.1%)and Singapore(5.8%).For yen-related transactions,Japan’s market share is25%, compared to28.3%for the U.K.(BIS,2007,Tables B.2and E.4).

changes have taken place in the global pecking order is necessarily the ?rst step in understanding what factors are responsible for such changes.

In this paper we measure price discovery in multiple markets that are sequential in time and non-overlapping (e.g.,Tokyo and London).The case of parallel markets where trading takes place simultaneously in different venues (e.g.,the NYSE and the NASDAQ)was ?rst examined in the seminal study by Hasbrouck (1995).The information share proposed by Hasbrouck (1995)measures the contribution of a particular market to the changes in the ef?cient price of an asset.An alternative approach taken up by Booth,So,and Tse (1999),Chu,Hsieh,and Tse (1999),and Harris,McInish,and Wood (2002),uses the permanent-transitory decomposition of Gonzalo and Granger (1995).Both approaches have been adopted by numerous studies of price discovery between parallel markets (e.g.,spot versus derivative trading,?oor versus electronic trading).Cross-market comparisons of price discovery have spawned into ‘‘a mid-sized cottage industry’’(Lehmann,2002).A special issue of the Journal of Financial Markets in 2002was devoted to the comparison between the two approaches.Pascual,Pascual-Fuster,and Climent (2006)expand the Hasbrouck model to distinguish trade-related versus trade-unrelated information shocks.New applications of the Hasbrouck and the Gonzalo-Granger models have continued to ?ourish.4

In parallel markets,price discovery occurs simultaneously in multiple venues;therefore it is dif?cult to achieve a clean separation of price innovations from different markets.This is well recognized in the literature (e.g.,Lehmann,2002).Recently Yan and Zivot (2010)use a structural cointegrated VAR to give new insights to the comparison between the Hasbrouck and Gonzalo-Granger models.Yan and Zivot (2007)propose to use the cumulative impulse responses from the structural cointegrated VAR to better capture the dynamics of price discovery.

Because the existing models are designed only for parallel markets,international comparisons of price discovery are often limited to one or two hours of overlapping trading time (e.g.,Hupperets and Menkveld,2002;Grammig,Melvin,and Schlag,2005;Pascual,Pascual-Fuster,and Climent,2006).In most cases,the closing of the home market overlaps with the opening of the overseas market,often the NYSE.The small overlapping hours may lead to bias against the newly-opened market as the newly-arrived traders learn from past price movements (see Hsieh and Kleidon,1996).Menkveld,Koopman,and Lucas (2007)develop a state-space model that takes into account prices from non-overlapping trading periods for partially overlapping markets.Currently there is no model designed for comparing price discovery across non-overlapping markets (e.g.,Tokyo vs.London or Shanghai vs.New York).Studies of non-overlapping markets (e.g.,Lieberman,Ben-Zion,and Hauser,1999;Agarwal,Liu,and Rhee,2007)focus on Granger causality between the prices without measuring their contributions to the ef?cient price.

We propose two approaches to measure price discovery in sequential non-overlapping markets.The basic logic behind the two approaches is the same as the Hasbrouck model:Information ?ow is measured by the variation in the ef?cient price of an asset.Changes in the ef?cient price are identi?ed as the random-walk component of the observed returns.The information share of a particular market is its share in the total variance of the ef?cient price in a trading day.The two approaches differ in how the variance of the

4

See for example Chakravarty,Gulen,and Mayhew (2004),Covrig,Ding,and Low (2004),Figuerola-Ferretti and Gonzalo (2010),Cao,Hanscah,and Wang (2008),and Harris,McInish,and Wood (2008).

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

84

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10885 ef?cient price is estimated.The?rst approach is based on the recent advances in estimating the integrated variance using high-frequency observations.We use the two-scales(TS) estimator of Zhang,Mykland,and A¨?t-Sahalia(2005),which is a consistent estimator of the integrated variance.The variance of the ef?cient price is estimated as the mean of the TS estimator.In addition to the information share,the ratio of the TS estimator to the realized variance provides a measure for the pricing ef?ciency of a market.Our second approach is based on a structural vector autoregressive(VAR)model for the open-to-close returns of sequential markets.This is particularly useful when intraday prices are not available,or when measuring information?ows during non-trading periods(e.g., overnight).Studies have shown signi?cant information?ow during non-trading periods. Our measure of the information contribution of each market is based on the market-speci?c shocks and has a clean interpretation.The structural VAR model has several advantages:it is very easy to implement,its data requirement is not onerous,and the empirical results do not depend on intraday sampling frequency and the noise-?ltering method used.The drawback of the structural VAR is that the intraday observations are not fully exploited for estimating the variance of the ef?cient price change.In our sample, the estimated information shares from the structural VAR are similar to those from realized variance.As discussed in Section3,combining our methods with those for parallel markets allows researchers to study the general case of partially overlapping markets. Our methods are applied to the foreign exchange markets,which trade continuously around the clock.By estimating the information shares across markets and time zones,we provide new evidence on exchange rate price discovery.There is indirect evidence that some markets are more important than others in currency trading.Ito,Lyons,and Melvin(1998)and Covrig and Melvin(2002)provide evidence of private information in currency trading and suggest that Tokyo may know more about the yen than other markets.However the?ndings are disputed by Andersen,Bollerslev,and Das(2001).We compare price discovery across global markets for AUD,JPY,EUR,and GBP,all against USD,for an eight-year period from January1996to December2003.These are the top-four currency pairs in trading value, representing58%of global currency trading(Bank for International Settlements(BIS),2007). A24-hour day is divided into four sequential markets(see Table1):‘‘Asia,’’‘‘Europe,’’the overlap between London and New York City labeled as‘‘LondontNYC,’’and‘‘U.S.,’’which covers trading in the Americas.The information shares of these markets are estimated using realized variance,as well as the structural VAR model.Sub-period analyses reveal changes in the contribution of each market over the eight years.The?ndings are summarized below: ‘‘Europe’’and‘‘LondontNYC’’have the highest pricing ef?ciency:over90%of the price variations are changes in the ef?cient price.Their combined information shares are 40–42%for AUD and JPY and51–53%for EUR and GBP.‘‘Asia’’has the lowest pricing ef?ciency among the four markets.Its information shares are28–33%for AUD and JPY and16–17%for EUR and GBP.‘‘U.S.’’takes up the remaining shares.

Over the sample period,price discovery appears to become more concentrated in ‘‘Europe,’’particularly in the‘‘LondontNYC’’trading hours.‘‘Asia’’lost shares in Asian currencies while‘‘U.S.’’remained stable.For JPY,the information share of ‘‘Asia’’declined from33%in1996–1999to28%in2000–2003.‘‘Europe’’increased its share from28%to31%and that of‘‘LondontNYC’’rose from12%to15%.The ?ndings suggest that Tokyo is not a leading information hub for JPY.The signi?cance of‘‘Mrs.Watanabe’’may have been overstated.

The two-hour ‘‘London tNYC’’period is highly signi?cant for currency trading.It has the highest per-hour information shares for all currencies.It gained information shares in all four currencies over the sample period.

Different measures of information shares give similar estimates of the signi?cance of a market.However the information share of a market can be very different from its share of trading volume.For example,‘‘Asia’’accounts for over half of AUD trading but less than one-third of AUD information share.In general,the share of the trading volume of the home market overstates its information share.

Although we do not examine what affects a market’s information share,evidence from microstructure studies of the foreign exchange markets offers some clues.Since the trading platform is the same,the difference between markets is in the number and characteristics of market participants.Studies have shown that order ?ows are the critical link between exchange rate changes and economic fundamentals (Evans and Lyons,2002a,2005,2007,2008);order ?ows from ?nancial institutions have greater information content than other investors (Bjonnes,Rime,and Solheim,2005;Carpenter and Wang,2007);and there are cross-market information ?ows between currencies (Evans and Lyons,2002b;Yan and Zivot,2007).Therefore a market’s information share depends on the quantity and the quality of its order ?ows.Such order ?ows tend to come from ?nancial institutions with a large client base and substantial research capacity.

The paper is organized as follows:Section 2presents the two approaches for measuring price discovery in sequential markets.Section 3explains the data and trading statistics in the foreign exchange markets.The estimation and empirical ?ndings in the currency markets are discussed in Section 4.Section 5is a brief summary.2.Measuring price discovery in sequential markets

Consider a single asset traded in two adjoining and non-overlapping markets during a 24-hour trading day.The scenario is depicted in Fig.1:market 1opens at the beginning of day t and closes at the point when market 2opens,while market 2closes at the beginning of day t t1.As discussed shortly,the setup can be easily modi?ed to allow overlapping markets or non-trading periods.The closing prices of markets 1and 2are p 1,t and p 2,t ,respectively.The end-of-day price is p t p 2,t .All prices are logarithms.The open-to-close returns of the markets are r 1,t =p 1,t àp 2,t à1and r 2,t =p 2,t àp 1,t ,and are subject to market-speci?c price innovations Z 1,t and Z 2,t .In terms of notation,the ?rst subscript i (i =1,2)indicates the market and the second subscript t (t =1,2,3,y )indicate the (24-hour)day.For the same t ,Z 1,t and p 1,t always occur before Z 2,t and p 2,t .The innovations Z 1,t and Z 2,t

1,t

p Trading time

Fig.1.Two sequential non-overlapping markets.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

86

represent ‘‘news’’and are uncorrelated with each other and over time.They may contain permanent shocks re?ecting unexpected changes in economic fundamentals,and transitory shocks resulting from short-term mispricing,liquidity shocks,or microstructure factors (e.g.,bid-ask bounce or inventory control).

The closing prices p i,t of each market can be written as p i,t =m i,t tu i,t ,i =1,2,where m i,t is the ef?cient price re?ecting new information on economic fundamentals,and u i,t is a noise term resulting from transitory factors.Changes in the ef?cient price in markets 1and 2are D m 1,t =m 1,t àm 2,t à1=h 1Z 1,t and D m 2,t =m 2,t àm 1,t =h 2Z 2,t ,where h 1and h 2are constants and can be estimated using daily observations,see Eq.(7).With respect to the information set available at the opening of market i on day t ,D m i,t is a martingale difference.Therefore,D m 1,t and D m 2,t are uncorrelated with each other and over time.They capture the information components in price innovations Z 1,t and Z 2,t .The change of the ef?cient price over day t is D m t =m 2,t –m 2,t à1=D m 1,t tD m 2,t .Following Hasbrouck (1995),information ?ow in market i is measured by the variance of D m i,t .Therefore the information share of market i is de?ned as

IS i ?

var eD m i ;t Tvar eD m t T?var eD m i ;t T

var eD m 1;t Ttvar eD m 2;t T

;

i ?1;2:

e1T

When the ef?cient price is treated as a continuous-time process,the conditional variance of its

change over a time interval is measured by the integrated variance (the instantaneous variance integrated over the time interval),see Andersen and Benzoni (2008).The integrated variance may be estimated for each day by using intraday observations.The variance of D m i,t can be expressed as the unconditional mean of the integrated variance of market i on day t .

In this section,we propose two ways to estimate var(D m i,t ).When intraday prices are available,it can be estimated by the mean value of an estimator of the integrated variance.This is discussed in Section 2.1.If intraday prices are not available,or one of the markets is a non-trading period (e.g.,overnight),var(D m i,t )can be estimated using the structural VAR model presented in Section 2.2.We use the two-market setup to demonstrate the methodology and note that it can be easily generalized to any number of sequential markets.If there is a non-trading period between two markets (e.g.,Hong Kong and New York),one can estimate the information shares of the three periods,including the non-trading period in the middle.Similarly,when two markets are partially overlapping (e.g.,Europe and the U.S.),they can be divided into three periods with the overlapping period in the middle.Our model can be used to estimate price discovery in the three sequential periods.5Price discovery in the overlapping period can be decomposed using models for parallel https://www.360docs.net/doc/ad17183169.html,rmation shares measured by realized variance

Our ?rst approach is based on the fast expanding literature on realized variance.6Market i can be divided into M i sampling intervals.Return in market i on day t over sampling interval s can be written as r i,t,s =D m i,t,s tD u i,t,s ,where D m i,t,s is the change in the ef?cient price over the sampling interval and represents a permanent shift in the asset value,and D u i,t,s captures intraday noise.When sampled at high frequency,i.e.,M i -N ,the sum of squared D m i,t,s ,P M i

s ?1D m 2i ;t ;s ,converges to the integrated variance in market i on

5

This is the approach taken in our empirical analysis of Europe and the U.S.

6We thank the editor and the referee for suggesting the use of realized variance for information shares.For a detailed discussion on realized variance,see Andersen and Benzoni (2008)and the references therein.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–10887

day t .However,the realized variance (RV),de?ned as RV i ;t P M i s ?1r 2

i ;t ;s ,is a biased and inconsistent estimator of the integrated variance in the presence of the noise term u i,t,s .Since the ef?cient price and the noise term are not observable,many studies have proposed ways to reduce or remove the impact of the noise term on the estimation of the integrated variance (e.g.,A ¨?t-Sahalia,Mykland,and Zhang,2005;Barndorff-Nielsen,Hansen,Lunde,and Shephard,2005;Zhang,Mykland,and A ¨?t-Sahalia,2005;Bandi and Russell,2006).The two-scales (TS)estimator of Zhang,Mykland,and A ¨?t-Sahalia (2005)appears to be the ?rst consistent estimator of the integrated variance.A ¨?t-Sahalia and Mancini (2008)show that the TS estimator unambiguously outperforms the RV in out-of-sample forecasting comparisons.Barndorff-Nielsen,Hansen,Lunde,and Shephard (2005)argue for the merits of the kernel-based estimators and show that the TS estimator can be expressed as a kernel-based estimator

RV E i ;t ?1àM i àH i M i eH i t1T

X M i s ?1r 2

i ;t ;s tX H i h ?1

1àh H i t1 X M i àh s ?h t1er i ;t ;s àh r i ;t ;s tr i ;t ;s th r i ;t ;s Tàv i ;t ;H i t1H i t1;

e2T

where H i is the number of ‘‘autocovariances.’’The adjustment factor v i ;t ;H i t1is recursively

de?ned by v i ,t ,1 0and v i ;t ;h v i ;t ;h à1ter i ;t ;1tááátr i ;t ;h à1T2ter i ;t ;M i àh à2tááátr i ;t ;M i T2for h =2,y ,H i t1.The TS estimator is in fact a linear combination of the standard RV at two different frequencies (two-scales):the highest frequency possible and a lower frequency.Since the RV consistently estimates the noise variance as sampling frequency goes to in?nity,the RV sampled at the high frequency is a good approximation to the noise variance.At the low frequency,many feasible RVs may be computed (e.g.,with 1-minute returns there are ?ve ways to construct 5-minute RV).The estimation error of the average of these RVs at the low frequency depends on the noise variance.The linear combination of the average of the low-frequency RVs and the high-frequency RV then serves to correct the impact of the noise term on the average of the low-frequency RVs and effectively lead to a consistent estimator of the integrated variance.The TS estimators RV E i ;t for market i on day t can be treated as a stationary time series with possibly strong autocorrelations (e.g.,Andersen,Bollerslev,Diebold,and Labys,2003;Corsi,2009;A ¨?t-Sahalia and Mancini,2008).The unconditional variance of the ef?-cient price var(D m i,t )may be estimated by the mean of the TS estimator,RV E i ?E eRV E i ;t T.Then the information share in (1)becomes

IS i eRV E

T?RV E

i RV E 1tRV E 2

;i ?1;2:e3T

The distribution of information shares across markets is denoted as IS (RV E ).For

comparison,we also calculate the information shares based on the standard RV,IS (RV ).7The mean of the TS estimator,RV E i ,may be estimated by the sample mean of the time series RV E i ;t .But the estimation error is not straightforward to quantify given that the time series RV E i ;t is generally strongly autocorrelated.Following the insight of Corsi (2009)that

7

An alternative approach to the non-parametric estimator is to explicitly model the intraday return as an autoregressive process.The intraday changes of the ef?cient price,extracted from the Beverage-Nelson (1981)decomposition,are then squared and summed to estimate the integrated variance.In our empirical application,this approach leads to results (not reported in this paper)similar to those based on the TS estimator.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

88

the realized variance series can be described as a heterogeneous AR process(which is a restricted parsimonious AR),we use an unrestricted VAR to model the time series behavior of the vector V t??RV E1;t;RV E2;t 0and estimate the mean values.8Speci?cally,the VAR is given by GeLTV t?aterror t,where G(L)is the AR lag polynomial matrix and a is a constant vector.The VAR is estimated by OLS.The mean of V t is given by G(1)à1a,with plug-in OLS estimates,and its components are used to compute(3).Further,a parametric bootstrap with block-error draws is use to quantify the estimation errors in(3).9The bootstrap procedure is given in Appendix A.

2.2.A structural VAR model for open-to-close returns

Asset returns over non-trading periods, e.g.overnights and weekends,have been examined since French(1980).Recent studies have shown substantial overnight information?ow.10If intraday prices are not available for a market,or one wants to compare price discovery between trading and non-trading periods,the above RV-based method is no longer feasible.In this case,the information shares of the two markets can be estimated from a structural VAR model using only open-to-close returns.

The basic idea behind the structural VAR is similar to the RV-based approach in Section 2.1.The goal is to estimation the variance of the ef?cient price changes for the sequential markets.We use a structural VAR to identify the random-walk component in the open-to-close returns and estimate its variance.Let r t=[r1,t,r2,t]0be the vector of open-to-close returns of the two markets in Fig.1.The dynamics of r t is modeled as a structural vector autoregressive process with K lags:11

B0r t?

X K

k?1

B k r tàktg te4T

where g t=[Z1,t,Z2,t]0.As discussed above,the structural shocks Z1,t and Z2,t capture the market-speci?c price innovations and are uncorrelated.The variance of the structural shocks is normalized to one.Therefore E(g t)=0;E(g t g0tàk)=0)for k a0;E(g t g0t)=I,

a2?2identity matrix.12B0is a lower triangular matrix B0?b110

b21b22

!

because the

markets are sequential:within the same trading day t,r1,t affects r2,t but not vice versa.The impact of market2on market1is captured by the lagged returns on the right hand of(4). 8The estimated mean values from VAR are almost the same as the sample means in our empirical study.

9The information shares may be alternatively estimated from the sample mean of V

t

with the standard errors being constructed via direct block-bootstrapping V t.Given that V t is strongly autocorrelated,this approach may be more sensitive to the block size than the parametric bootstrap with block-error draws.

10See for example Cao,Ghysels,and Hatheway(2000),Davies(2003),Barclay and Hendershott(2003,2004, 2008).Cliff,Cooper,and Gulen(2008)report a striking?nding that the US equity premium in recent years is solely due to overnight returns.

11We do not consider cross-currency impact,e.g.from JPY returns to AUD returns.Such consideration requires a high-dimensional VAR model of parallel trading of different currencies.The main dif?culty is the identi?cation of currency-speci?c shocks.The lack of a cross-currency model is a limitation of the current study as it can potentially reveal a common source of price discovery for multiple currencies.Cross-currency information ?ows have been documented by Evans and Lyons(2002b)and Yan and Zivot(2007).

12An alternative and equivalent parameterization is to normalize the diagonal elements of B

as unity and leave the variance of Z t as a positive diagonal matrix.

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10889

In the real world,the sequence of the markets is set by their trading hours in calendar time.In Appendix B,we show that the model outcomes are invariant to the choice of the start of the 24-hour trading cycle.

Eq.(4)can be written in the reduced form

r t ?

X K k ?1

A k r t àk te t or A eL Tr t ?e t ;e5T

where A k ?B à10B k ;A eL T?I àA 1L àáááàA K L K

;L is the lag operator;the roots of 9A (z )9=0are outside the unit circle.The reduced-form shock e t satis?es e t ?B à10g t ?110

b 12b 22

!g t with E(e t )=0,(E(e t e 0t àk )=0for k a 0,E ee t e 0t T?eB 00B 0Tà1?X .The lag

polynomial A (L )and the covariance matrix X can be estimated using least squares.Since B 0is lower triangular and X is symmetric,the elements of B 0are exactly identi?ed by eB 00B 0Tà1?X and can be estimated by using the lower triangular Cholesky factor of the least squares estimator of X .

The VAR in (5)has a moving average representation in the form of Beverage-Nelson (1981)decomposition

r t ?A eL Tà1e t ?A e1Tà1

e t tC eL Tee t àe t à1T

with C eL T?

X 1j ?0

C j L j

where A e1T?I àA 1àáááàA K ,C eL T??A eL Tà1àA e1Tà1 =e1àL Tand C j converges to zero

exponentially as j increases.The daily return (over 24hours)is obviously r 1,t tr 2,t

=0

r t ,

where is a vector of ones.The end-of-day price p t is the sum

of 0r t over t =1,y ,t and may be written as 13

p t ?p 0

t0

A e1T

à1

X

t t ?1

e t te t ?p 0

t0A e1Tà1

B à1

X t t ?1

g t te t

e t

?0C eL Te t

?

0X 1j ?0

C j e t àj

?

0X 1j ?0

C j B à1

0g t àj

where p 0is determined by the initial conditions at t =0.The term e t represents pricing

errors and is stationary.The ef?cient price is de?ned as

m t ?lim q -1

E ep t tq 9

F t T?p 0

t0

A e1Tà1

B à10

X

t t ?1

g t e6Twhere F t is the information set at the end of day t .The daily change in the ef?cient price

D m t ?m t àm t à1

?0A e1Tà1B à10g t ?h 0

g t ?h 1Z 1;t th 2Z 2;t

e7T

is a combination of the structural shocks in two markets,and h 0??h 1;h 2

?0A e1Tà1B à1

0is the vector of the impact coef?cients of the two shocks.The h coef?cients here incorporate the long-run effects A (1)à1,equivalent to the cumulative impulse response of in?nite steps.

13

Note that unlike r t ,which is a 2?1vector,the end-of-day price p t is a scalar and equals p 2,t .

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

90

Based on the structural VAR,the information share14in(1)becomes

IS ieSVART?vareh i Z i;tT

vareD m tT

?

h2

i

h2

1

th2

2

;i?1;2:e8T

The cross-market distribution of information shares is denoted as IS(SVAR).

The IS(SVAR)is based on the impact of structural shocks that are market-speci?c,while most existing models are based on reduced-form shocks.From(5),the reduced-form shocks e1,t and e2,t are functions of the independent structural shocks:e1;t?b11Z1;t and e2;t?b21Z1;ttb22Z2;t where b ij are the elements of Bà10.Eq.(7)implies that D m t?

Ae1Tà1e t?d0e t?d1e1;ttd2e2;t,and vareD m tT?d2

1varee1;tTtd2

2

varee2;tTt2d1d2covee1;t;e2;tT.

The contributions of the reduced-form shocks e1,t and e2,t cannot be unambiguously separated unless they are uncorrelated.Therefore,using reduced-form VAR to compute information shares is appropriate only when the correlations among the reduced-form shocks can be ignored.The structural model outlined above provides a clean separation of price innovations in sequential markets,while the structural model of Yan and Zivot (2007)provide a clean separation between permanent and transitory shocks in parallel https://www.360docs.net/doc/ad17183169.html,pared to the state-space model of Menkveld,Koopman,and Lucas(2007), our model is extremely easy to implement:least squares estimation of(4)and the Cholesky factorization of?X are suf?cient for the measure in(8).The estimation errors of the information shares are quanti?ed using the bootstrap procedure detailed in Appendix A.

3.Global currency markets and data summary

The global currency markets can be treated as the sequential markets described in Section2.

A common asset,e.g.the Japanese yen,is traded24hours a day across Asia,Europe,and the United States time zones.The trading platform is identical across all markets.While the determinants of currency values are not well understood,15they are more susceptible to global risk factors than most other assets.For example,the link between the value of the Australian dollar and commodity prices is widely acknowledged by academics and market practitioners. Greater volatility in commodity prices may shift the price discovery of the Australian dollar from Sydney to London or New York where commodity trading is concentrated.We implement the models in Section2to estimate the information shares of different markets in currency trading and explore how the signi?cance of each market has changed over time.

The exchange rates we study are AUD,JPY,EUR,and GBP against USD.Our data source is the Reuters’intraday foreign exchange quotes for these rates from1January1996 (1January1999for EUR)to31December2003.As conventional in studies of currency trading,weekends are removed because of thin trading.We also remove days with large gaps(over4hours)in quote arrivals,which can be the result of system stoppage or holidays in parts of the world.On October7and8,1998,JPY had‘‘once-in-a-generation’’volatility,and both AUD and GBP experienced high volatility.16These days are treated as 14An alternative measure,termed the component share(CS),is often used by studies based on the Gonzalo-Granger (1995)model.A similar measure for our structural model is CS i=h i/(h1th2),i=1,2.

15The disconnection between exchange rates and domestic macroeconomic fundamentals are well established since Meese and Rogoff(1983).See Lyons(2001)for the new micro exchange rate economics.

16On October7,1998,JPY jumped from around130to120per USD in one day.See Cai,Cheung,Lee,and Melvin(2001)for events surrounding these days.

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10891

outliers and are removed from our analyses.This leaves us with 1884days for AUD,1902days for JPY,1189days for EUR,and 1879days for GBP.

We divide the 24hours into four sequential markets based on their time zones.In addition to the three conventional time zones in Asia,Europe,and the Americas,the overlapping trading hours in London and New York City are singled out as a separate market due to its special signi?cance in currency trading.The four markets are de?ned in Table 1,which lists the local time in various markets relative to the Greenwich Mean Time (GMT).The bold letters are local trading hours from 9am to 4pm local time.Market 1is the Asian trading hours from the start of 23GMT to the end of 6GMT in the next day,and is labeled as ‘‘Asia’’.Market 2is the European trading from the start of 7GMT to the end of 12GMT.It covers most of the trading hours in Frankfurt and Zurich and is labeled as ‘‘Europe’’.Market 3is the overlap of London afternoon and New York morning trading from 13to 14GMT and is labeled as ‘‘London tNYC’’.Market 4is from the start

Table 1

De?nitions of four sequential markets.

This table divides a 24-hour calendar day into four sequential markets:‘‘Asia’’from 23to 6GMT,‘‘Europe’’from 7to 12GMT,‘‘London tNYC’’from 13to 14GMT,and ‘‘U.S.’’from 15to 22GMT.The bold letters denote local trading hours.Markets

GMT Sydney Tokyo Hong Kong/Singapore

Frankfort/Zurich

London New York

San Francisco

010********A 111109322118S 2121110432219I 3131211542320A

414131265021515141376122616151487223E 71716159830U 818171610941R 9191817111052O 10201918121163P 11212019131274E 12222120141385London 13232221151496tNYC

140232216151071510231716118162101817129U 1732119181310S

1843220191411195432120151220654222116132176523221714228760231815ASIA

23

9

8

7

1

19

16

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

92

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10893 Table2

Average daily transactions.

This table reports the average daily transactions in April2007in top10foreign exchange markets.It is constructed from Bank for International Settlements(BIS),(2007,Table E.5).Transactions include spot,outright forward,and swap transactions against USD and are measured in billion USD.

AUD JPY EUR GBP

Value Percent Value Percent Value Percent Value Percent Australia76.733.413.5 2.523.5 2.213.5 3.0 Denmark0.460.2 1.890.420.9 1.9 1.740.4 France 5.89 2.613.0 2.448.2 4.49.92 2.2 Germany 1.250.59.29 1.743.0 3.97.03 1.6 Hong Kong14.0 6.116.4 3.120.2 1.912.6 2.8 Japan10.6 4.6138.825.825.7 2.47.62 1.7 Singapore15.7 6.843.18.047.9 4.421.2 4.7 Switzerland 6.12 2.720.7 3.974.0 6.828.6 6.3 United Kingdom55.924.3153.628.6443.640.7240.353.3 United States30.913.594.017.5179.116.477.117.1

Asia in Top10117.051.0211.839.4117.310.754.912.2 Europe in Top1069.630.3198.536.9629.757.7287.663.8 Top10217.594.7504.393.8926.184.9419.693.1 Global total229.6100537.51001091.2100450.8100 of15GMT to the end of22GMT and covers the Americas excluding‘‘LondontNYC’’. Since the United States is the only one in the top-ten markets(Table2),market4is labeled as‘‘U.S.’’.

Table2reports the average daily trading values of the four currency pairs in top-10 currency markets.It is constructed from the triennial survey conducted by the Bank for International Settlements(BIS),(2007,Table E.5).Although the reported trading values are not divided into the four markets de?ned in Table1,it gives a broad picture of the distribution of the trading values over a24-hour trading day.Five of the top10are in Europe and four are in Asia.AUD trading is more concentrated in Asia(51%), particularly in Australia(33.4%).There is more JPY-USD trading in U.K.(28.6%)than in Japan(25.8%),as in the case of all JPY-related transactions.JPY trades are more evenly split between Asia(39.4%)and Europe(36.9%).EUR and GBP are dominated by Europe and U.K.in https://www.360docs.net/doc/ad17183169.html,’s trading shares in EUR and GBP are much lower than those of U.S.These ten markets account for over93%of world trading of AUD,JPY,and GBP, and84.9%of world trading of EUR.

https://www.360docs.net/doc/ad17183169.html,rmation shares in currency trading

This section reports the empirical estimation of the information shares of the four sequential markets:‘‘Asia’’,‘‘Europe’’,‘‘LondontNYC’’,and‘‘U.S.’’.The?rst two sub-sections report the estimated information shares based on realized volatility and the structural VAR model,respectively.We then present evidence on the information shares of per-hour trading and the changes of information shares over the eight-year sample period.

https://www.360docs.net/doc/ad17183169.html,rmation shares based on realized variance:IS(RV E )

To estimate RV and RV E ,intraday returns at various sampling intervals are constructed.We sample the intraday Reuters quotes at 1,2,5,10,15,20,30,and 60minutes intervals.The midpoint of the bid and ask quotes at the end of each sampling interval is computed as the linear interpolation of the mid-quotes immediately before and after the end of the interval.17The return in market i on day t at time s ,r i ,t ,s ,is calculated as 100times the log ratio of the prices at time s and s à1.The daily realized variance for market i ,RV i,t ,i =1,y ,4,is the sum of the squared r i ,t ,s over its trading hours.

Fig.2presents the average daily RV at different sampling intervals,termed the signature plot.The pattern of RV at different sampling intervals is very similar to those reported in other studies,e.g.Hansen and Lunde (2006).As discussed in Section 2.1,the estimated RV is largely driven by noise when sampled at ultra high frequencies.For example,at 1-minute sampling interval the realized variance has a high noise component.The average RV declines as the sampling interval increases.It becomes stable when the sampling interval is higher than 30minutes for AUD,JPY,EUR,and 15minutes for GBP.We use the 30-minute RV,denoted as RV 30m ,as the daily RV.As we see later,there is still a signi?cant noise component in RV even with 30-minute sampling.

The two-scales estimator,RV E i ,calls for the use of the highest sampling frequency.In

our case,it is estimated using 1-minute sampling and is denoted as RV E

1m .The number of the ‘‘autocovariance’’terms,H i in Eq.(2),is set at 6,which is approximately the value computed from the popular formula of Newey and West (1994)for the Bartlett kernel;see also Hansen and Lunde (2006,p139).With the daily RV i ;t E series (market i on day t ),the daily information share may be de?ned as IS i ;t ?RV E i ;t =P j RV E j ;t .18The time series plots of the daily RV E i ;t and IS i,t for JPY

0.0

0.10.20.30.40.50.60.70.80

R e a l i z e d V o l a t i l i t y (x 104)

JPY

AUD

EUR

GBP

Sampling Intervalin Minute

10

20304050

60

Fig.2.Signature plots of realized volatility.

17

One drawback of the linear interpolation is that when the sampling interval goes to zero,the return and the realized variance reduce to zero (Hanson and Lunde,2006).An alternative approach is to use the mid-quote immediately before the end of an interval.The drawback here is the possibility of stale price.Both methods are widely used in the literature.We use the linear interpolation because we do not sample at ultra high frequencies and we are concerned of stale price,especially for AUD.18

We thank the referee for suggesting this and the use of unit-root tests to check stationarity.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

94

are presented in Fig.3,where each daily series ?uctuates at an approximately constant level and there is no visible trend.The plots for other currencies are not presented because of similarity.The sample statistics for RV E i ;t and IS i,t are presented in Table 3.The augmented Dickey-Fuller test convincingly rejects the null hypothesis of a unit root in any of the daily series,whereas the Ljung-Box Q statistic suggests that all daily series have strong autocorrelations.Because of the autocorrelations,the sample standard deviations in Table 3are not suitable for statistical inferences.

Table 4reports the estimated mean values of daily RV E

1m and RV 30m for the four

markets.Since RV E

1m and RV 30m are highly persistent,the mean values are estimated from a VAR model and their standard errors are estimated from the bootstrap procedure in Appendix A with 1000replications.The lag length of the VAR,G eL TV t ?a terror t ,is selected by the Akaike Information Criterion (AIC)from a maximum 32,where V t is the

Asia

Europe

London+NYC

U.S.

Asia

Europe

London+NYC

U.S.

01230.0

0.20.40.60.80.2

0.40.60.80

12340.0

0.51.01.50.0

0.51.01.50.0

0.20.40.60.80.0

0.20.40.60.81996

1998

2000

2002

2004

1996

1998

2000

2002

2004

1996

1998

2000

2002

2004

1996

1998

2000

2002

2004

1996

1998

2000

2002

2004

1996

1998

2000

2002

2004

Fig.3.Plots of daily RV E 1m and IS eRV E 1m Tfor JPY:(a)daily RV E 1m for JPY and (b)daily IS eRV E

1m Tfor JPY.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

95

vector of RVs of the four markets on day t .For (AUD,JPY,EUR,GBP),the selected lag

lengths are (9,19,23,8)for RV E 1m and (8,8,5,8)for RV 30m ,respectively.As RV E

1m is a reasonable proxy for the information ?ow (the variance of the ef?cient price change)and

RV 30m contains both information and noise,the ratio RV E

1m =RV 30m provides a measure of

Table 3

Summary of sample statistics of daily RV E

1m and information share.

This table reports the sample mean,sample standard deviation (Stddev),Ljung-Box Q statistic for 10lags (Q LB (10)),and augmented Dickey-Fuller unit-root test statistic (ADFstat)of daily realized variances and

information shares.The 1%critical value for ADFstat is à3.96.Here RV E

1m is the daily TS estimator of the

integrated variance at 1-minute sampling interval and IS (RV E 1m )is the daily information share based on RV E

1m .

Asia

Europe

London tNYC

U.S.

AUD

RV E 1m

Mean 0.1270.1270.0550.141Stddev 0.1370.1280.0740.148Q LB (10)11281603699857ADFstat à11.5à10.6à8.93à10.8IS (RV E 1m )Mean 0.2830.2850.1190.314Stddev 0.1290.1140.0760.131QLB(10)34938.030.584.2ADFstat à13.3à30.0à29.5à14.2JPY

RV E 1m Mean 0.1520.1350.0580.116Stddev 0.2380.1960.0800.125QLB(10)112612813211548ADFstat à12.6à11.0à14.1à9.5IS (RV E 1m )Mean 0.3040.2970.1340.265Stddev 0.1390.1180.0890.124Q LB (10)19413965.798.6ADFstat à26.0à13.7à28.1à21.0EUR

RV E 1m Mean 0.0720.1420.0690.133Stddev 0.1070.2360.0680.121Q LB (10)62.7134171296ADFstat à21.1à9.98à12.6à14.8IS (RV E 1m )Mean 0.1770.3290.1670.327Stddev 0.1030.1290.0980.135Q LB (10)13215936.4206ADFstat à16.0à13.0à22.8à12.4GBP

RV E 1m Mean 0.0350.0850.0330.072Stddev 0.0370.0770.0290.055Q LB (10)3771021348.6558ADFstat 15.610.514.211.9IS (RV E 1m )Mean 0.1600.3700.1500.320Stddev 0.0900.1200.0800.130Q LB (10)17920445.3307ADFstat

à12.1

à20.3

à30.4

à13.4

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

96

market-speci?c pricing ef?ciency.Table 4shows that for all currencies and all markets,the

ratio RV E

1m =RV 30m are less than one,implying that RV 30m contains considerable noise,ranging from 6%to 34%.Using this measure for the pricing ef?ciency,there is a remarkably consistent ordering in the pricing ef?ciency:‘‘Europe’’has the highest ef?ciency for all four currencies,followed by ‘‘London tNYC’’and ‘‘U.S.’’.Asia has the lowest pricing ef?ciency across the four markets.

The estimated information shares IS i (RV E

1m )are reported in Table 5.As in Table 4,the associated standard errors are calculated from the bootstrap.All of the estimated information shares are statistically different from zero.There are several features in the table.First,if the 24hours are divided into three 8-hour time zones,then the European time zone,which includes ‘‘Europe’’and ‘‘London tNYC’’de?ned in Table 1,dominates price discovery in currency trading.The combined information shares of ‘‘Europe’’and ‘‘London tNYC’’range from 40.6%for AUD to 52.8%for GBP.The two-hour ‘‘London tNYC’’trading accounts for a signi?cant portion of price discovery in this time

Table 4

Estimated mean of daily realized variance.

This table reports the estimated mean of daily realized variance and the associated standard error,using the

method of Appendix A.RV E 1m =RV 30m is the ratio of the estimated means of RV E 1m and RV 30m ,respectively.RV E

1m is the TS estimator of the integrated variance at 1-minute sampling interval.RV 30m is the realized variance of the observed price at 30-minute sampling interval.The intraday returns are the difference in log prices over the sampling interval,multiplied by 100.

Asia

Europe London tNYC

U.S.AUD

RV E 1m 0.127

0.1280.0550.141St.err.0.0110.0110.0050.011RV 30m 0.1820.1410.0630.166St.err.

0.0180.0130.0050.014RV E 1m =RV 30m (%)70918785JPY

RV E 1m 0.1510.1340.0580.114St.err.0.0210.0170.0050.013RV 30m 0.2030.1430.0650.14St.err.

0.0240.0160.0050.012RV E 1m =RV 30m (%)74948981EUR

RV E 1m 0.0700.1420.0690.131St.err.0.0070.0190.0060.014RV 30m 0.0990.1530.0750.165St.err.

0.0100.0130.0050.010RV E 1m =RV 30m (%)71939279GBP

RV E 1m 0.0350.0850.0330.072St.err.0.0020.0050.0020.003RV 30m 0.0530.0950.0390.088St.err.

0.0050.0060.0020.004RV E 1m =RV 30m (%)

66

89

85

82

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–10897

zone.‘‘Europe’’generally has greater information shares than ‘‘U.S.’’.The exception is AUD which may re?ect price discovery in AUD futures contracts traded on the Chicago Mercantile Exchange.

Second,the information shares of ‘‘Asia’’are 28.2%for AUD and 33.1%for JPY.Therefore around 70%of permanent price changes in these currencies occur outside of Asia.It seems unlikely that Tokyo knows more about the yen than others.Our results do not support a signi?cant role from Japanese retail investors.The information shares of ‘‘Asia’’are much lower for EUR and GBP.

Third,a market’s high pricing ef?ciency may not translate into high information shares.If a market with high pricing ef?ciency has low information ?ow,it may not have high information shares.Even though the pricing ef?ciency of ‘‘Asia’’is similar for AUD and EUR (Table 4),the low information share of ‘‘Asia’’in EUR trading may be the result of low information ?ow regarding EUR in Asia time zone.

Fourth,the information shares of a market are generally different from its share of trading values in Table 2.For example,Asia accounts for 51%of AUD trading but only 28%in AUD information ?ow.In general,trading volume tends to overstate the signi?cance of the home market in the pricing of local https://www.360docs.net/doc/ad17183169.html,rmation shares based on the structural VAR:IS(SVAR)

For each market de?ned in Table 1,the open-to-close returns are calculated from the Reuters’intraday quotes.For example,‘‘Europe’’opens at the start of 7GMT and closes at the end of 12GMT.The opening price is the interpolation of the mid-quotes immediately before and after 7GMT.The closing price is the opening price of ‘‘London tNYC’’,which is the interpolation of the mid-quotes immediately before and after 13GMT.The open-to-close return for ‘‘Europe’’is the difference of the two log

Table 5

Information shares based on TS estimator.

This table reports the estimated information shares based on the TS estimator of the integrated variance at

1-minute sampling interval,IS eRV E

1m T.The estimation is based on equation (3)and the bootstrap procedure that follows.

Asia

Europe London tNYC U.S.AUD

IS eRV E

1m T(%)28.228.312.231.3St.err.0.0070.0050.0040.007JPY

IS eRV E

1m T(%)33.129.312.625.0St.err.0.0110.0080.0060.007EUR

IS eRV E

1m T(%)17.034.516.731.8St.err.0.0080.0140.0070.011GBP

IS eRV E

1m T(%)15.637.814.731.9St.err.

0.005

0.008

0.003

0.008

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

98

J.Wang,M.Yang/Journal of Financial Markets14(2011)82–10899 Table6

Summary of open-to-close returns.

The de?nitions of markets are given in Table1.Open-to-close returns in the four markets are de?ned as 100?[ln(Q LB)–ln(P open)].Q LB(10)is the Ljung-Box statistic for10lags.The asterisk n indicates signi?cant at5% level.

Asia Europe LondontNYC U.S. AUD

Meanà0.007à0.0060.0010.005 Stddev.0.3610.3600.2540.348 Skewnessà0.2460.270à0.117à0.395 Kurtosis7.6011.44 6.90 5.82 Q LB(10)11.0913.64 4.8023.20n Correlation

Europe0.010

LDN-NYCà0.068nà0.073n

U.S.0.061nà0.029à0.007

JPY

Meanà0.006à0.009à0.0020.018 Stddev.0.4240.3920.2620.323 Skewness0.034à0.640à0.503à0.048 Kurtosis8.958.7011.407.16 Q LB(10)31.03n13.3324.29n13.54 Correlation

Europeà0.018

LDN-NYCà0.0170.0006

U.S.0.005à0.084n0.015

EUR

Mean0.006à0.0400.0160.029 Stddev.0.2600.4150.2830.373 Skewnessà0.6460.5790.019à0.051 Kurtosis8.457.12 4.83 5.52 Q LB(10)13.6410.3018.50n21.56n Correlation

Europeà0.068n

LDN-NYCà0.003à0.081n

U.S.0.027à0.0120.091n

GBP

Meanà0.006à0.0190.0160.020 Stddev.0.1780.2990.1970.264 Skewnessà0.287à0.0650.035à0.118 Kurtosis8.42 5.07 4.90 6.15 Q LB(10) 5.5413.65 5.0410.66 Correlation

Europeà0.064n

LDN-NYCà0.003à0.042n

U.S.0.031à0.0040.073n

prices.Table 6reports the summary statistics.Similar to Table 4,AUD and JPY have high volatility during Asia trading while EUR and GBP have high volatility during the European market.19EUR and GBP have greater volatility during the two-hour ‘‘London tNYC’’than during the eight-hour trading in ‘‘Asia’’.Both show high levels of skewness and kurtosis in Asia.The Ljung-Box Q-statistic shows that JPY and EUR have signi?cant same-market autocorrelations while GBP shows no autocorrelation.Returns in the London tNYC period are often negatively correlated with returns in other markets.JPY returns in Asia have strong autocorrelation but no cross-market correlation.When estimating the structural VAR model,the number of lags is determined by the AIC criterion,and is one for AUD and GBP,?ve for JPY,and two for EUR.The reduced-form VAR of Eq.(5)is estimated via least squares.The structural coef?cient B à1

is obtained from the Cholesky factorization of the estimated covariance matrix X .The price

impact coef?cients are h 0??h 1;h 2;h 3;h 4

?0A e1Tà1B à1

0.The IS (SVAR )is calculated from (8).Standard errors are based on bootstraps with 1000replications.

The results of the structural VAR are presented in four segments in Table 7for AUD,JPY,EUR,and GBP,respectively.The top panel of each segment presents the estimated

structural coef?cients matrix B à1

0.For all four exchange rates,at least one of the off-diagonal elements of B à10is statistically different from zero.

20Therefore the covariance matrix X is not diagonal,and the reduced-form shocks e t in Eq.(5)are correlated across markets.As discussed before,it is critical to use the structural model in this case in order to separate market-speci?c price innovations.

The bottom panel of each segment in Table 7reports the estimated information shares and statistical inference.Across the four markets,‘‘Asia’’has the highest information shares for AUD and JPY,and ‘‘Europe’’has the highest information shares for EUR and GBP.However the combined ‘‘Europe’’and ‘‘London tNYC’’trading period has the highest information shares for all four currencies.‘‘U.S.’’has much higher information shares than ‘‘Asia’’in EUR and GBP.The standard errors are estimated from the bootstrap procedure in Appendix A.Even though some of the estimated information shares are small,e.g.8.1%for EUR in ‘‘Asia’’,all of them are signi?cantly greater than zero.The 90%con?dence intervals are narrow enough to allow for statistical comparisons between information shares of different markets.

Table 8compares the estimated IS eRV E

1m Twith IS (SVAR ).Comparisons are based on the mean absolute difference (MAD)between the estimated information shares of the same market and the Spearman’s rank correlation across markets (Rank Cor.).Except for

AUD,cross-market rankings based on IS eRV E

1m Tand IS (SVAR )are similar and rank correlations are high at 0.8or 1.The MAD for AUD is reasonably small;therefore the low rank correlation for AUD is driven by small numerical differences in the values across markets that are of similar magnitudes.Overall IS (SVAR )and IS (RV E )are broadly

consistent with each other.Since RV E

1m utilizes the intraday high-frequency data and is

based on a consistent estimator of the daily market-speci?c integrated variance,IS eRV E

1m Tappears more desirable than IS (SVAR )and should be used when high-frequency data are available.However,if high-frequency data are not available,or one of the markets is a non-trading period,the structural VAR based IS (SVAR )is the only feasible choice.

19

Note that Table 4reports the realized variance while Table 6reports the sample standard deviations of open-to-close returns.20The standard errors of B à10coef?cients are not reported here to conserve space.

J.Wang,M.Yang /Journal of Financial Markets 14(2011)82–108

100

Table7

Information shares based on the structural VAR model.

The de?nitions of markets are given in Table1.IS(SVAR)is the information share estimated from the structural VAR model.The number of lags K is determined by the Akaike Information Criterion.

Asia Europe LondontNYC U.S.

AUD

Structural coef?cients Bà1

with K=1lag

Asia0.359n

Europe0.0030.360n

LondontNYCà0.016nà0.018n0.253n

America0.021nà0.009à0.0030.346n IS(SVAR)(%)33.129.613.124.3 St.err.0.0300.0280.0200.023 Lower5%0.2820.2490.1000.207 Upper5%0.3810.3400.1650.283 JPY

Structural coef?cients Bà1

0with K=5lags

Asia0.416n

Europeà0.0040.386n

LondontNYCà0.005à0.0010.259n

U.S.0.006à0.026n0.0050.319n

IS(SVAR)(%)30.927.920.320.9 St.err.0.0600.0440.0400.051 Lower5%0.2140.2100.1430.131 Upper5%0.4080.3520.2710.296

EUR

Structural coef?cients Bà1

0with K=2lags

Asia0.256n

Europeà0.026n0.412n

LondontNYCà0.001à0.023n0.281n

U.S.0.007à0.0020.029n0.365n

IS(SVAR)(%)8.144.321.026.6 St.err.0.0360.0420.0310.038 Lower5%0.0330.3660.1630.207 Upper5%0.1480.5040.2690.336

GBP

Structural coef?cients Bà1

with K=1lag

Asia0.176n

Europeà0.017n0.297n

LondontNYCà0.001à0.0080.196n

U.S.0.009à0.0010.020n0.263n

IS(SVAR)(%)13.638.817.330.2 St.err.0.0200.0250.0240.024 Lower5%0.1060.3490.1380.260 Upper5%0.1700.4320.2150.339 J.Wang,M.Yang/Journal of Financial Markets14(2011)82–108101

青年教师基本功大赛演讲稿

首届“教育教学技能大比武”总结 为期半个月的青年教师首届“教育教学技能大比武”活动已经圆满落下帷幕。参加本次比赛的教师都是38周岁以下的青年教师,比赛内容包括讲课、答辩、三笔字、演讲四个环节。这次活动在学校领导的大力支持下,在全体教师的努力配合下,在参赛教师积极参与、认真准备下,取得圆满成功。 回顾本次比赛活动,老师们无论是在个人综合素质、教材把握能力还是在课堂驾驭能力上都有精彩的展示,下面对本次活动做一个总结: 一、讲课赛环节 这十九位青年教师对此次比赛高度重视,认真备课、讲课,为我们呈现了一节节风格各异、亮点纷呈的课,主要呈现了一下几个特点: 1、备课充分、设计用心。 老师们在备课过程中,能深入钻研教材,做了大量充分的准备。老师们都精心设计导语,创设情境,千方百计地激发起学生强烈的求知欲,能够把知识和能力深入浅出又扎扎实实的传授给学生,每一节课都朴实无华,每一节课都独具匠心,比如:郑珊老师在讲授《图形的旋转》一课时,教学设计层次分明,抓住平移和旋转的特征明确其描述方法,在新授的过程中能够放手让学生自己思考-动手操作-小组交流-展示(说明描述),老师引导学生亲历学习过程,通过几个有效的追问,使自己体会掌握了学习内容。 2、教学扎实有效,注重基础训练。 老师们能够抓住教学目标,精心设计每一个环节,同时老师们十分注重基础训练,比如高年级语文老师在教学中注重字词的品读与指导,在阅读教学中,老师能通过阅读来领悟文本的内涵,例如王玉英讲述《梅花魂》一课,她更注重引导学生“品词、品句、品读”以此让学生以读明理,以读悟情,通过“品”字让学生真正体会到了外祖父为什么那么珍爱墨梅图,从而理解梅花的品行,上升到中国人的气节。语文中低年级教学中,教师注重字形的书写字文的理解和区别运用,比如赵彤霞老师执教《植物妈妈有办法》一课,能在文中恰到好处的让学生理解“许多”和“许”“多”的区别,并用“纷纷”说一句话。又比如赵志芳执教《秋天的雨》一课中,注重了“爽”字的书写指导,教学中注重句子的训练,让学生练说比喻句。 3、注重学生情感态度和学习习惯的培养。 注重学生情感态度和学习习惯的培养是成为这次比赛课的又一亮点。老师们在教学中,做到自始至终关注学生的情感,营造宽松、民主、和谐的教学气氛,尊重每个学生,积极鼓励他们在学习中的尝试,保护他们的自尊心和积极性。比如吴蕊霞老师的鼓励具有个性化,激励性的语言常挂嘴边,成为学生不断学习、创新不可缺乏的精神动力。同时在教学中注重学习习惯的培养,比如高月枝老师在授课的同时适时对学生进行了课常规的教育,整个一节课,教学秩序井然有序,对于刚上学两个星期的孩子真的很难得。 4、善用多媒体教学。 本次讲课赛几乎所有的老师都制作了精美实用的多媒体课件,追求既生动形象又快捷高效的教学效果。特别是赵丽和龚伟科两位老师用我们上学期培训的知识制作了白板课件。 5、教师素养良好。 通过这次比赛,我们欣喜地看到我校青年教师具备良好的教师基本素质。他们教态大方得体,语言清晰,具有较强的亲和力和应变能力。王敏、陈蓉等老师她们在课堂上文雅得体的教态,丰富的肢体语言以及亲切和蔼的微笑,都给我们留下了深刻的印象,深受学生的喜爱。 针对本次讲课赛反映出的问题,给老师们提出以下建议,跟老师们商榷:1、语文教学中,略读课文的教学教师应大胆放手学生,让学生充分展示自己。有感情的朗读,重在先理解再

The way常见用法

The way 的用法 Ⅰ常见用法: 1)the way+ that 2)the way + in which(最为正式的用法) 3)the way + 省略(最为自然的用法) 举例:I like the way in which he talks. I like the way that he talks. I like the way he talks. Ⅱ习惯用法: 在当代美国英语中,the way用作为副词的对格,“the way+ 从句”实际上相当于一个状语从句来修饰整个句子。 1)The way =as I am talking to you just the way I’d talk to my own child. He did not do it the way his friends did. Most fruits are naturally sweet and we can eat them just the way they are—all we have to do is to clean and peel them. 2)The way= according to the way/ judging from the way The way you answer the question, you are an excellent student. The way most people look at you, you’d think trash man is a monster. 3)The way =how/ how much No one can imagine the way he missed her. 4)The way =because

教师基本功大赛即兴演讲稿

教师即兴演讲题目之63个话题 来源:思雨教育资源网|教学资源|课件论文|作文作者:无边思雨发表日期:2009-5-30 13:16:19 阅读次数: 910 查看权限:普通文章 1、如何维护班集体荣誉? 2、如何看待学生时代早恋问题? 3、成人与成才二者是怎样的关系?结合实例说明自己的观点。 4、不同地域、不同背景、不同习惯的同学之间该如何相处? 5、怎样面对学习、生活中遇到的挫折? 6、你最崇拜的人是谁?“名人”还是自己? 7、你认为我们是否应有感恩之心?感恩于谁? 8、你希望自己会是怎样一位老师?你会如何教育自己的学生? 9、“言行、仪表”与个人的发展。 10、如今继续提倡“勤俭、节约”作风是否已过时? 11、在各种资料、媒体中常讲张扬个性,你认为我们该张扬什么样的个性? 12、三轮车工人方尚礼自己生活的如乞丐,却将自己蹬车收入的35万多元用来资助失学儿童,当病重时,社会捐助给他治病的钱,也被他捐给了希望工程。你对方尚礼的这种行为有何评述? 13、电视广告不宜过多 14、保护环境是每个人的责任 15、我中学时代的一个朋友 16、世界需要热心肠 17、向权威挑战 18、2008年的我 19、我爱电视广告 20、我的母亲 21、尊重是孩子成长的基石 22、如何培养学生的好奇心 23、推广普通话 24、“恶语伤人六月寒” 25、我心中的偶像 26、假如我是画家 27、童年趣事 28、珍惜现在 29、我最爱看的电视节目 30、有人认为老师是不断燃烧的蜡烛,你认为呢? 31、新课程背景下良好师生场的营造。 32、让谐趣幽默走进我们的课堂。 33、阅读教学中如何开展有效的对话教学? 34、如何正确处理价值取向和个性化阅读的关系? 35、新课程背景下一堂好课的标准是什么? 36、“语文教学工具性与人文性统一”的内涵是什么? 37、如何实践语文教学的人文性和工具性的“统一”? 38、如何挖掘教材资源,准确选点,扎实训练?

The way的用法及其含义(二)

The way的用法及其含义(二) 二、the way在句中的语法作用 the way在句中可以作主语、宾语或表语: 1.作主语 The way you are doing it is completely crazy.你这个干法简直发疯。 The way she puts on that accent really irritates me. 她故意操那种口音的样子实在令我恼火。The way she behaved towards him was utterly ruthless. 她对待他真是无情至极。 Words are important, but the way a person stands, folds his or her arms or moves his or her hands can also give us information about his or her feelings. 言语固然重要,但人的站姿,抱臂的方式和手势也回告诉我们他(她)的情感。 2.作宾语 I hate the way she stared at me.我讨厌她盯我看的样子。 We like the way that her hair hangs down.我们喜欢她的头发笔直地垂下来。 You could tell she was foreign by the way she was dressed. 从她的穿著就可以看出她是外国人。 She could not hide her amusement at the way he was dancing. 她见他跳舞的姿势,忍俊不禁。 3.作表语 This is the way the accident happened.这就是事故如何发生的。 Believe it or not, that's the way it is. 信不信由你, 反正事情就是这样。 That's the way I look at it, too. 我也是这么想。 That was the way minority nationalities were treated in old China. 那就是少数民族在旧中

(完整版)the的用法

定冠词the的用法: 定冠词the与指示代词this ,that同源,有“那(这)个”的意思,但较弱,可以和一个名词连用,来表示某个或某些特定的人或东西. (1)特指双方都明白的人或物 Take the medicine.把药吃了. (2)上文提到过的人或事 He bought a house.他买了幢房子. I've been to the house.我去过那幢房子. (3)指世界上独一无二的事物 the sun ,the sky ,the moon, the earth (4)单数名词连用表示一类事物 the dollar 美元 the fox 狐狸 或与形容词或分词连用,表示一类人 the rich 富人 the living 生者 (5)用在序数词和形容词最高级,及形容词等前面 Where do you live?你住在哪? I live on the second floor.我住在二楼. That's the very thing I've been looking for.那正是我要找的东西. (6)与复数名词连用,指整个群体 They are the teachers of this school.(指全体教师) They are teachers of this school.(指部分教师) (7)表示所有,相当于物主代词,用在表示身体部位的名词前 She caught me by the arm.她抓住了我的手臂. (8)用在某些有普通名词构成的国家名称,机关团体,阶级等专有名词前 the People's Republic of China 中华人民共和国 the United States 美国 (9)用在表示乐器的名词前 She plays the piano.她会弹钢琴. (10)用在姓氏的复数名词之前,表示一家人 the Greens 格林一家人(或格林夫妇) (11)用在惯用语中 in the day, in the morning... the day before yesterday, the next morning... in the sky... in the dark... in the end... on the whole, by the way...

“the way+从句”结构的意义及用法

“theway+从句”结构的意义及用法 首先让我们来看下面这个句子: Read the followingpassageand talkabout it wi th your classmates.Try totell whatyou think of Tom and ofthe way the childrentreated him. 在这个句子中,the way是先行词,后面是省略了关系副词that或in which的定语从句。 下面我们将叙述“the way+从句”结构的用法。 1.the way之后,引导定语从句的关系词是that而不是how,因此,<<现代英语惯用法词典>>中所给出的下面两个句子是错误的:This is thewayhowithappened. This is the way how he always treats me. 2.在正式语体中,that可被in which所代替;在非正式语体中,that则往往省略。由此我们得到theway后接定语从句时的三种模式:1) the way+that-从句2)the way +in which-从句3) the way +从句 例如:The way(in which ,that) thesecomrade slookatproblems is wrong.这些同志看问题的方法

不对。 Theway(that ,in which)you’re doingit is comple tely crazy.你这么个干法,简直发疯。 Weadmired him for theway inwhich he facesdifficulties. Wallace and Darwingreed on the way inwhi ch different forms of life had begun.华莱士和达尔文对不同类型的生物是如何起源的持相同的观点。 This is the way(that) hedid it. I likedthe way(that) sheorganized the meeting. 3.theway(that)有时可以与how(作“如何”解)通用。例如: That’s the way(that) shespoke. = That’s how shespoke.

way 用法

表示“方式”、“方法”,注意以下用法: 1.表示用某种方法或按某种方式,通常用介词in(此介词有时可省略)。如: Do it (in) your own way. 按你自己的方法做吧。 Please do not talk (in) that way. 请不要那样说。 2.表示做某事的方式或方法,其后可接不定式或of doing sth。 如: It’s the best way of studying [to study] English. 这是学习英语的最好方法。 There are different ways to do [of doing] it. 做这事有不同的办法。 3.其后通常可直接跟一个定语从句(不用任何引导词),也可跟由that 或in which 引导的定语从句,但是其后的从句不能由how 来引导。如: 我不喜欢他说话的态度。 正:I don’t like the way he spoke. 正:I don’t like the way that he spoke. 正:I don’t like the way in which he spoke. 误:I don’t like the way how he spoke. 4.注意以下各句the way 的用法: That’s the way (=how) he spoke. 那就是他说话的方式。 Nobody else loves you the way(=as) I do. 没有人像我这样爱你。 The way (=According as) you are studying now, you won’tmake much progress. 根据你现在学习情况来看,你不会有多大的进步。 2007年陕西省高考英语中有这样一道单项填空题: ——I think he is taking an active part insocial work. ——I agree with you_____. A、in a way B、on the way C、by the way D、in the way 此题答案选A。要想弄清为什么选A,而不选其他几项,则要弄清选项中含way的四个短语的不同意义和用法,下面我们就对此作一归纳和小结。 一、in a way的用法 表示:在一定程度上,从某方面说。如: In a way he was right.在某种程度上他是对的。注:in a way也可说成in one way。 二、on the way的用法 1、表示:即将来(去),就要来(去)。如: Spring is on the way.春天快到了。 I'd better be on my way soon.我最好还是快点儿走。 Radio forecasts said a sixth-grade wind was on the way.无线电预报说将有六级大风。 2、表示:在路上,在行进中。如: He stopped for breakfast on the way.他中途停下吃早点。 We had some good laughs on the way.我们在路上好好笑了一阵子。 3、表示:(婴儿)尚未出生。如: She has two children with another one on the way.她有两个孩子,现在还怀着一个。 She's got five children,and another one is on the way.她已经有5个孩子了,另一个又快生了。 三、by the way的用法

青年教师朗诵比赛活动方案

青年教师朗诵比赛活动方案 (2014----2015)学年度下学期 一、活动目的: 学校是推广普通话,规范语言文字的主阵地,教师作为推广普通话的中坚力量有着不可忽视的重要作用。因此,为了加强教师基本功训练,提升教师的朗读水平,教导处根据语言文字规范化活动计划,开展以“朗读美文展我风采”的教师朗诵比赛。通过教师美文朗读比赛,提高我校青年教师普通话水平,营造浓厚的校园读书氛围,提升教师教学基本功,促使教师重视朗读教学,促进学生健康和谐发展。 二、活动组织:教导处 三、具体活动安排: 1、培训时间:6月8日(周一)下午14:30 2、比赛时间:6月15日(周一)下午14:30 3、比赛地点:四楼舞蹈室 4、参赛人员:35岁以下(含35岁)青年教师必须参加,同时欢迎35岁以上教师参加。 5、比赛内容:作品自选,体裁不限(不少于三分钟) 6、比赛形式:可配乐,参赛人员独立诵读。 7、评委:黄冬梅蒋丽丽郭艳华贺芳刘忠霞冷静武玉德 8、分数统计:王辉赵慧贤

9、主持:徐金凤 四、活动程序: 1、学校将在赛前一周邀请校长对参赛人员进行培训。 2、参赛教师提前十分钟到达比赛场地,做好准备工作。 3、14:40正式进行比赛,按抽签顺序进行。 4、评分办法:比赛采取现场评分的办法,满分10分,比赛结束后,进行分数汇总、统计,取平均分,宣布比赛成绩。 5、校长点评并作总结。 五、设奖情况: 本次比赛将设一等奖2名,二等奖3名,三等奖5名,优秀奖若干名。比赛成绩计入年末教师量化考核。 六、朗诵比赛评分标准 (一)、主题内容(2分) 1、内容(1分):题材不限,内容健康向上;充实生动,有真情实意 2、主题(1分):寓意深刻,富有感召力 (二)、普通话(3分) 1、发音(1分):语音准确1分,较准确0.8分,基本准确0.5分,不准确不得分。 2、语速(1分):语速恰当、声音洪亮,表达自然流畅1分,因不熟练,每停顿一次扣0.1分。

教师基本功即兴演讲需要准备几分钟

青年教师基本功大赛即兴演讲题目【题目1】我的兴趣爱好【题目2】谈谈内心和谐【题目3】人最难超越的高度就是自己【题目4】我的价值观【题目5】谈谈与人相处【题目6】坚守心灵的一方沃土【题目7】给快乐找个理由【题目8】年轻 没有什么不可以【题目9】心底无私天地宽【题目10】人是需要一点精神的【题目11】我们与时代同行【题目12】生活从“心”开始【题目13】让更多的人快乐 【题目14】面对繁杂的教学工作 你如何调整心态 【题目15】和谐、健康、快乐【题目16】我喜爱的书刊【题目17】你如何发展自己的专业弱点【题目18】善待自己 呵护希望【题目18】.上公开课对一个教师的成长的作用【题目19】培养积极心态 感悟责任人生【题目24】永不言弃 我心永恒 准备时间 3分钟 【题目25】.你怎样做个身心健康的老师【题目26】你如何看待家长满意工程 【题目27】新课程执行过程中 你碰到最棘手的问题是什么【题目28】课堂教学中 你最关注的是什么【题目29】你希望学校领导关心青年教师哪些方面【题目30】谈谈自己的业余生活【题目31】简评最近的工作情况。【题目32】怎样才能提高教师的凝聚力。【题目33】.谈谈做班主任的心得【题目34】.你怎样定义教师【题目35】简介杨森中学【题目36】.点评一位我校的优秀教师【题目37】.如何看待家长的不理解【题目38】.谈谈卫生与健康【题目39】谈谈我校的环境. 【题目40】谈谈如何管理学生【题目41】谈谈你对职业道德的认识【题目42】我参加校本研修之感想。【题目43】“依法治教 注重服务 着力塑造行业形象” 请你谈谈你的设想【题目44】.如何发挥你校师生之特长 【题目45】.怎样调动老师的工作积极性 【题目46】.谈谈你对校本教研的看法。【题目47】.我是怎样备课的。【题目48】.维持校门口的秩序 我的一点想法。【题目49】如何丰富教师的业余生活 缓解教师的心理压力 【题目50】谈谈你对节日文化的认识【题目51】学校活动很多的情况下 你如何调节自己的心态 【题目52】德育倡导“全面德育 全员德育” 请你谈谈自己的理解。【题目53】如何让家长尊重教师 【题目54】你认为提高教育质量应从哪里抓起【题目55】从哪些方面帮助班主任管理学生篇二:教师即兴演讲题目之63个话题 教师即兴演讲题目之63个话题 来源:思雨教育资源网|教学资源|课件论文|作文作者:无边思雨发表日期:2009-5-30 13:16:19 阅读次数: 910 查看权限:普通文章 1、如何维护班集体荣誉? 2、如何看待学生时代早恋问题? 3、成人与成才二者是怎样的关系?结合实例说明自己的观点。 4、不同地域、不同背景、不同习惯的同学之间该如何相处? 5、怎样面对学习、生活中遇到的挫折? 6、你最崇拜的人是谁?“名人”还是自己? 7、你认为我们是否应有感恩之心?感恩于谁? 8、你希望自己会是怎样一位老师?你会如何教育自己的学生? 9、“言行、仪表”与个人的发展。 10、如今继续提倡“勤俭、节约”作风是否已过时? 11、在各种资料、媒体中常讲张扬个性,你认为我们该张扬什么样的个性? 12、三轮车工人方尚礼自己生活的如乞丐,却将自己蹬车收入的35万多元用来资助失学儿童,当病重时,社会捐助给他治病的钱,也被他捐给了希望工程。你对方尚礼的这种行为有何评述? 13、电视广告不宜过多 14、保护环境是每个人的责任

The way的用法及其含义(一)

The way的用法及其含义(一) 有这样一个句子:In 1770 the room was completed the way she wanted. 1770年,这间琥珀屋按照她的要求完成了。 the way在句中的语法作用是什么?其意义如何?在阅读时,学生经常会碰到一些含有the way 的句子,如:No one knows the way he invented the machine. He did not do the experiment the way his teacher told him.等等。他们对the way 的用法和含义比较模糊。在这几个句子中,the way之后的部分都是定语从句。第一句的意思是,“没人知道他是怎样发明这台机器的。”the way的意思相当于how;第二句的意思是,“他没有按照老师说的那样做实验。”the way 的意思相当于as。在In 1770 the room was completed the way she wanted.这句话中,the way也是as的含义。随着现代英语的发展,the way的用法已越来越普遍了。下面,我们从the way的语法作用和意义等方面做一考查和分析: 一、the way作先行词,后接定语从句 以下3种表达都是正确的。例如:“我喜欢她笑的样子。” 1. the way+ in which +从句 I like the way in which she smiles. 2. the way+ that +从句 I like the way that she smiles. 3. the way + 从句(省略了in which或that) I like the way she smiles. 又如:“火灾如何发生的,有好几种说法。” 1. There were several theories about the way in which the fire started. 2. There were several theories about the way that the fire started.

教师基本功是教师从事教育教学工作必须具备的最基本的职业技能分析

教师基本功是教师从事教育教学工作必须具备的最基本的职业技能。它包括通用于所有教师的一般基本功,也包括学科教学和教育工作的基本功。教师基本功是加强青年教师职业道德建设的一项重要内容,也是教师从事教育教学工作必须具备的最基本的职业技能。如果说教学是技术加艺术,那么这种技术和艺术主要表现在教师课堂教学的基本功上面。它是教师素质的重要表现,也是教学成败的关键。过去所说的教师基本功,无非是三字一画(钢笔、毛笔、粉笔字和简笔画)和语文基础知识、口头表达能力等,再加上一些专业学科的基本功(音乐、体育、美术等)。在新一轮的课程改革中,需要我们重新看待教师的教学基本功。随着时代的发展,教师基本功的含义越来越广,教 师基本功包括的范围越来越大。下面我谈谈自己对教师应该具备的基本功的认识。 一、为人师表教师基本功应以德为先,教师的基本素质首当其冲的是师德素质。 我认为教师首先要有高尚的师德,只有思想上以学生为本,有做名师的愿望,至少有一个积极健康的心态,才能练好基本功。 1、有理想,有事业心。 2、以身作则学校无小事,处处皆教育,教师一言一行都会对学生造成影响。 二、爱的能力教师做的是人的工作,应该有人文素质,在爱

人过程中进行教育教学工作。爱学生也是一种技能,爱他们,使他们 容易、愉悦接受。 三、表达能力. 1、语言表达普通话是教师的职业语言,教师能用普通话进 行教学,普通话一般应达到国家语委制定的《普通话水平测试》二级水平。 2、文字表达教师的工作比较繁重,但是要学会反思和总结, 把心得体会写出来,才能少走弯路,更快进步,摆脱烦琐;才能轻松、高效的工作。 四、动手能力. 1、三笔一画这是传统意义的教师基本功。 2、板书板书不仅表现出一位教师上课的基本功,而且也体现教师的教学态度乃至性格。 3、运用、制作教具使用、制作教具方面,能按教学要求,正确使用教具;能就地取材,制作简易的教具。 4、现代信息技术的掌握和运用。 5、演示一般教师的演示指教态,教师也要做一个演员。 五、备课能力

way 的用法

way 的用法 【语境展示】 1. Now I’ll show you how to do the experiment in a different way. 下面我来演示如何用一种不同的方法做这个实验。 2. The teacher had a strange way to make his classes lively and interesting. 这位老师有种奇怪的办法让他的课生动有趣。 3. Can you tell me the best way of working out this problem? 你能告诉我算出这道题的最好方法吗? 4. I don’t know the way (that / in which) he helped her out. 我不知道他用什么方法帮助她摆脱困境的。 5. The way (that / which) he talked about to solve the problem was difficult to understand. 他所谈到的解决这个问题的方法难以理解。 6. I don’t like the way that / which is being widely used for saving water. 我不喜欢这种正在被广泛使用的节水方法。 7. They did not do it the way we do now. 他们以前的做法和我们现在不一样。 【归纳总结】 ●way作“方法,方式”讲时,如表示“以……方式”,前面常加介词in。如例1; ●way作“方法,方式”讲时,其后可接不定式to do sth.,也可接of doing sth. 作定语,表示做某事的方法。如例2,例3;

教师基本功是什么

教师基本功是什么1 我们常说“教学基本功”如何如何,多指教师的专业功底,教学基本技能,教学方法以及由此产生的教学效果等等,放在一个讨论教师质量和教育教学质量的背景下,我们是不是关注一下:什么是教师基本功呢? 基本素质 教师的基本素质首当其冲的是师德素质。师德不能等同于职业道德,但却函盖职业道德。我觉得职业道德主要是针对物品或没生命的,或有生命也不是传道授业与做人思想工作的。教师的职业道德重要的在于“师”字上,即为人师的职业道德。只是时下还有多少人能够有称职的师德呢?!当下的教育环境下,教师一方面普遍出现职业倦怠,一方面却又师德开始退化!教师的现状让人担忧! 我觉得,教师的基本素质应还包括人文素养,没有人文素养的教师眼中根本就不会有“人”的存在,也就不会在新课程中体现“以人为本”的理念,更不会在课堂上有“生命的气息”!我觉得人文素养应该尊重生命、尊重人的尊严,还要包括带头遵守社会文明公约、法律法规等,并成为践行的时代先锋。也就是说,教师还要在遵守社会文明等方面真正为人师表! 基本知识 教师职业的特殊性,必然要求每一个教师要具备一定的基本知识,即包括教育理论、学科知识、心理学知识等。教师教育理论的丰厚与否往往束缚一个教师的发展与理论素养的高低,甚至影响到教师的教育思想与个人成长;而学科知识除了学科的相关基础知识外,还应包括学科的前沿知识;因为现在的学生压力大,心理又非常脆弱,这就给教师的教育工作增加了难度,因此,教师的基本知识应该要有心理辅导的知识,再说,当下的教师工作压力大,许多教师心理也存在一定的问题,他们本身更需要心理的自我调适能力。 基本能力 教师应具备的基本能力是什么呢?我认为应该是学习能力、科研能力、解决问题能力、写作能力、组织教学能力、协作能力等。 知识日新月异,特别是网络的盛行,让知识的传播与创新更快,因此,教师如果没有学习能力,就不能与时俱进,便会成为时代的落后者,这会影响到教师自身的发展与教育水平高低。况且,现在对于终身教育或终身学习理念的倡导,作为一名教师更应该成为这一理念的先驱。 科研能力是不是教师的必备能力?或者说教师要不要搞教育科研?我觉得不一定每一个教师都要成为研究型教师与专家型教师,但具备一定的教育科研能力,或了解教育科研的方法,或参与并体验科学研究的过程,应该是教师要积极投入的一种体验。而且,当前新课程提倡的探究性学习或研究性学习,本身就是要培养学生的科学素养与科学精神!如果教师不具备

小学英语教师基本功比赛朗读材料-MY DREAM

小学英语教师基本功比赛朗读材料-MY DREAM My Dream Everyone has a lot of dreams. Some people want to be rich, dreaming of becoming millionaires [m?lj?'ne?] overnight. Others want to be famous, dreaming of suddenly jumping to great fame. I have a lot of dreams,too. When I was a young girl, I dreamed of becoming a scientist like Hua Iuogen in future. However, I knew very well that I could not succeed without painstaking ['pe?nzte?k??]efforts. So I studied hard in the middle school and college in order to attain my goal. After graduating from college, I found a job as a teacher. Although I was very busy with teaching, I never gave up my goal. I read a lot of books to get more knowledge. I made experiments to practice and apply what I had learnt from the books. Sometimes, I was so deeply indulged [?n'd?ld?] in my research that I forgot my meals and time. Now I have made great progress. Several of my research papers have been published. The methods ['meθ?d] proposed in my papers have been proven

the-way-的用法讲解学习

t h e-w a y-的用法

The way 的用法 "the way+从句"结构在英语教科书中出现的频率较高, the way 是先行词, 其后是定语从句.它有三种表达形式:1) the way+that 2)the way+ in which 3)the way + 从句(省略了that或in which),在通常情况下, 用in which 引导的定语从句最为正式,用that的次之,而省略了关系代词that 或 in which 的, 反而显得更自然,最为常用.如下面三句话所示,其意义相同. I like the way in which he talks. I like the way that he talks. I like the way he talks. 一.在当代美国英语中,the way用作为副词的对格,"the way+从句"实际上相当于一个状语从句来修饰全句. the way=as 1)I'm talking to you just the way I'd talk to a boy of my own. 我和你说话就象和自己孩子说话一样. 2)He did not do it the way his friend did. 他没有象他朋友那样去做此事. 3)Most fruits are naturally sweet and we can eat them just the way they are ----all we have to do is clean or peel them . 大部分水果天然甜润,可以直接食用,我们只需要把他们清洗一下或去皮.

演讲稿之教师基本功即兴演讲

教师基本功即兴演讲 【篇一:青年教师基本功大赛即兴演讲题目】 青年教师基本功大赛即兴演讲题目【题目1】我的兴趣爱好【题目2】谈谈内心和谐【题目3】人最难超越的高度就是自己【题目4】 我的价值观【题目5】谈谈与人相处【题目6】坚守心灵的一方沃 土【题目7】给快乐找个理由【题目8】年轻?没有什么不可以 【题目9】心底无私天地宽【题目10】人是需要一点精神的【题目11】我们与时代同行【题目12】生活从“心”开始【题目13】让更 多的人快乐?【题目14】面对繁杂的教学工作?你如何调整心态 ?【题目15】和谐、健康、快乐【题目16】我喜爱的书刊【题目17】你如何发展自己的专业弱点【题目18】善待自己?呵护希望 【题目18】.上公开课对一个教师的成长的作用【题目19】培养积 极心态?感悟责任人生【题目24】永不言弃?我心永恒?准备时间 ?3分钟?【题目25】.你怎样做个身心健康的老师【题目26】你如何看待家长满意工程?【题目27】新课程执行过程中?你碰到最棘 手的问题是什么【题目28】课堂教学中?你最关注的是什么【题目29】你希望学校领导关心青年教师哪些方面【题目30】谈谈自己的 业余生活【题目31】简评最近的工作情况。【题目32】怎样才能 提高教师的凝聚力。【题目33】.谈谈做班主任的心得【题目34】. 你怎样定义教师【题目35】简介杨森中学【题目36】.点评一位我 校的优秀教师【题目37】.如何看待家长的不理解【题目38】.谈谈 卫生与健康【题目39】谈谈我校的环境. 【题目40】谈谈如何管理 学生【题目41】谈谈你对职业道德的认识【题目42】我参加校本 研修之感想。【题目43】“依法治教?注重服务?着力塑造行业形 象”?请你谈谈你的设想【题目44】.如何发挥你校师生之特长? 【题目45】.怎样调动老师的工作积极性?【题目46】.谈谈你对校 本教研的看法。【题目47】.我是怎样备课的。【题目48】.维持校 门口的秩序?我的一点想法。【题目49】如何丰富教师的业余生活 ?缓解教师的心理压力?【题目50】谈谈你对节日文化的认识【题 目51】学校活动很多的情况下?你如何调节自己的心态?【题目52】德育倡导“全面德育?全员德育”?请你谈谈自己的理解。【题目53】如何让家长尊重教师?【题目54】你认为提高教育质量应从哪里抓 起【题目55】从哪些方面帮助班主任管理学生 【篇二:教师基本功即兴演讲需要准备几分钟】

way的用法总结大全

way的用法总结大全 way的用法你知道多少,今天给大家带来way的用法,希望能够帮助到大家,下面就和大家分享,来欣赏一下吧。 way的用法总结大全 way的意思 n. 道路,方法,方向,某方面 adv. 远远地,大大地 way用法 way可以用作名词 way的基本意思是“路,道,街,径”,一般用来指具体的“路,道路”,也可指通向某地的“方向”“路线”或做某事所采用的手段,即“方式,方法”。way还可指“习俗,作风”“距离”“附近,周围”“某方面”等。 way作“方法,方式,手段”解时,前面常加介词in。如果way前有this, that等限定词,介词可省略,但如果放在句首,介词则不可省略。

way作“方式,方法”解时,其后可接of v -ing或to- v 作定语,也可接定语从句,引导从句的关系代词或关系副词常可省略。 way用作名词的用法例句 I am on my way to the grocery store.我正在去杂货店的路上。 We lost the way in the dark.我们在黑夜中迷路了。 He asked me the way to London.他问我去伦敦的路。 way可以用作副词 way用作副词时意思是“远远地,大大地”,通常指在程度或距离上有一定的差距。 way back表示“很久以前”。 way用作副词的用法例句 It seems like Im always way too busy with work.我工作总是太忙了。 His ideas were way ahead of his time.他的思想远远超越了他那个时代。 She finished the race way ahead of the other runners.她第一个跑到终点,远远领先于其他选手。 way用法例句

the_way的用法大全教案资料

t h e_w a y的用法大全

The way 在the way+从句中, the way 是先行词, 其后是定语从句.它有三种表达形式:1) the way+that 2)the way+ in which 3)the way + 从句(省略了that或in which),在通常情况下, 用in which 引导的定语从句最为正式,用that的次之,而省略了关系代词that 或 in which 的, 反而显得更自然,最为常用.如下面三句话所示,其意义相同. I like the way in which he talks. I like the way that he talks. I like the way he talks. 如果怕弄混淆,下面的可以不看了 另外,在当代美国英语中,the way用作为副词的对格,"the way+从句"实际上相当于一个状语从句来修饰全句. the way=as 1)I'm talking to you just the way I'd talk to a boy of my own. 我和你说话就象和自己孩子说话一样. 2)He did not do it the way his friend did. 他没有象他朋友那样去做此事. 3)Most fruits are naturally sweet and we can eat them just the way they are ----all we have to do is clean or peel them . 大部分水果天然甜润,可以直接食用,我们只需要把他们清洗一下或去皮. the way=according to the way/judging from the way 4)The way you answer the qquestions, you must be an excellent student. 从你回答就知道,你是一个优秀的学生. 5)The way most people look at you, you'd think a trashman was a monster. 从大多数人看你的目光中,你就知道垃圾工在他们眼里是怪物. the way=how/how much 6)I know where you are from by the way you pronounce my name. 从你叫我名字的音调中,我知道你哪里人. 7)No one can imaine the way he misses her. 人们很想想象他是多么想念她. the way=because 8) No wonder that girls looks down upon me, the way you encourage her. 难怪那姑娘看不起我, 原来是你怂恿的

相关文档
最新文档