Table 1 Order book characteristics BHP NAB NCP TLS WOW Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. sprd 1.075 0.311 2.175 1.516 1.277 0.599 1.006 0.079 1.485 0.922 trvol 2,746.7 7,688.5 1,174.1 2,901.3 1,113.7 4,131.5 8,877.5 39,414.2 1,646.7 4,906.6 buyvol 5,692.4 9,783.9 2,830.6 4,016.9 4,817.5 7,408.2 2,1233.8 57,399.5 3,707.5 7,184.2 sellvol 8,336.2 12,190.6 2,902.7 3,902.7 5,358.7 7,789.6 21,816.1 60,877.4 4,410.3 6,785.4 qvol 8,303.4 38,223.4 3,534.3 4,858.5 5,235.3 6,238.4 35,513.0 68,337.0 4,832.7 7,329.7 qavol 9,704.9 12,842.4 3,621.1 5,169.3 5,209.8 6,058.5 35,077.7 68,038.8 5,123.8 7,046.5 qbvol 7,212.8 49,667.3 3,453.4 4,549.0 5,264.2 6,436.2 35,927.5 68,618.7 4,585.3 7,553.3 cvol 11,172.2 81,984.5 4,308.8 6,063.3 4,533.8 5,999.2 61,007.7 97,236.4 6,021.8 9,469.3 cavol 11,595.3 17,307.7 4,348.3 6,392.8 4,315.7 5,438.5 64,477.8 100,813.0 5,793.7 8,761.2 cbvol 10,778.7 112,671.2 4,271.5 5,736.1 4,774.1 6,553.5 58,166.4 94,120.8 6,211.8 10,018.1 d_askp 5.842 86.084 6.407 24.454 7.247 52.743 3.198 11.616 4.818 16.021 d_bidp 4.662 16.628 8.543 71.853 6.131 14.328 2.377 7.798 4.104 14.611 amq 0.115 0.316 0.423 0.809 0.101 0.319 0.040 0.197 0.230 0.518 avol 1,452.4 343.7 265.1 62.1 920.6 256.4 5,409.2 1,558.8 501.8 185.0 bvol 1,376.9 665.7 222.9 78.7 720.3 216.3 6,237.1 1,647.8 344.5 230.7 adiff_1 0.897 0.671 2.018 1.926 1.271 0.939 0.577 0.268 1.376 1.323 adiff_2 1.308 1.007 2.880 2.752 1.884 1.319 0.643 0.357 2.001 1.931 142 A. D. Hall, N. Hautsch
Table 1 (cont<strong>in</strong>ued) BHP NAB NCP TLS WOW Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. BHP NAB NCP TLS WOW Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. adiff_5 2.717 2.116 5.829 5.403 3.712 2.340 0.866 0.565 4.024 3.415 bdiff_1 0.898 0.650 1.851 1.700 1.155 0.869 0.582 0.273 1.187 1.032 bdiff_2 1.269 0.954 2.523 2.381 1.633 1.204 0.656 0.371 1.546 1.409 bdiff_5 2.488 1.948 4.806 4.639 3.077 2.078 0.937 0.612 2.781 2.610 adep_1 22.257 10.725 2.404 1.870 11.055 7.154 102.651 35.792 6.352 4.686 adep_2 34.429 21.732 3.614 3.262 15.621 12.257 196.338 77.341 9.862 8.665 adep_5 45.662 40.078 4.577 5.093 18.572 16.865 420.273 216.059 12.729 14.358 bdep_1 20.477 13.596 2.093 1.697 9.203 5.613 117.936 39.229 4.516 4.183 bdep_2 31.411 23.779 3.228 2.924 13.874 10.131 223.766 85.101 7.479 7.465 bdep_5 42.927 38.160 4.293 4.507 17.876 15.783 455.945 240.004 11.290 12.538 Means and standard deviations <strong>of</strong> various order book characteristics based on the BHP, NAB, NCP, TLS and WOW stock traded at the ASX. The samples conta<strong>in</strong> all market and limit orders <strong>of</strong> the <strong>in</strong>dividual stocks traded at the ASX dur<strong>in</strong>g July–August 2002, correspond<strong>in</strong>g to 45 trad<strong>in</strong>g days. All prices are measured <strong>in</strong> cents. The order book characteristics are: Bid-ask spread (sprd), traded volume (trvol), traded buy/sell volume (buyvol, sellvol), quoted volume (qvol), quoted ask/bid volume (qavol, qbvol), cancelled volume (cvol), cancelled ask/bid volume (cavol, cbvol), difference between quoted ask price and the current best ask price (d_askp), difference between current best bid quote and quoted bid price (d_bidp), absolute mid-quote change (amq), as well as cumulated ask/bid volume (avol, bvol, <strong>in</strong> units <strong>of</strong> 1,000 shares). Furthermore, adiff_x=px,a−mq, where px,a denotes the price associated with the x%-quantile <strong>of</strong> the cumulated ask volume and mq denotes the mid-quote. Correspond<strong>in</strong>gly, bdiff_x=mq-p x,b, where p x,b denotes the price associated with the x%-quantile <strong>of</strong> the cumulated bid volume. Moreover, adep_x =(x/100)·avol/(px,a−mq) and bdep_x =(x/100)·bvol/(mq−px,b), measured <strong>in</strong> units <strong>of</strong> 1,000 shares Order aggressiveness and order book dynamics 143
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High Frequency Financial Econometri
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Prof. Luc Bauwens CORE Voie du Roma
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vi Contents Intraday stock prices,
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2 L. Bauwens et al. component nicel
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4 L. Bauwens et al. but provides al
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Luc Bauwens . Dagfinn Rime . Genaro
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Exchange rate volatility and the mi
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32 K. Bien et al. Although economet
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34 K. Bien et al. 2.1 Copula functi
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36 K. Bien et al. and x k t ≡ (xk
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38 K. Bien et al. Fig. 3 Multivaria
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40 K. Bien et al. Bivariate model s
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42 K. Bien et al. deviation 0.0099,
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44 K. Bien et al. - Set ˆzt = Âxt
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46 K. Bien et al. % Frequency −0.
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48 K. Bien et al. References Amilon
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50 1 Introduction A. Escribano and
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52 A. Escribano and R. Pascual Jang
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54 A. Escribano and R. Pascual the
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56 The generating processes of mark
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58 with AtðLÞ ¼ 0 B @ 1 ð ÞAab
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60 A. Escribano and R. Pascual cros
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62 Hasbrouck (1991). The system is
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64 unitary seller-initiated shock (
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66 6.1 Estimation of the baseline m
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Table 2 The base-line VEC model for
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70 Table 3 Simulation of the base-l
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72 revert towards narrow levels. As
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Table 5 Impulse-response functions
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76 We also show that NYSE buyer-ini
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78 As 0 < a m < 1; L ð Þ ¼ 1 a m
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80 NYSE 2000 Stocks AOL America Onl
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82 A. Escribano and R. Pascual Madh
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84 1 Introduction S. Frey, J. Gramm
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86 develops the empirical methodolo
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Table 1 Sample descriptives Company
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90 comparability across stocks, we
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- Page 110 and 111: 104 To obtain the estimates in the
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- Page 114 and 115: 108 In the main text we discuss the
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- Page 144 and 145: 138 An important determinant of liq
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- Page 166 and 167: 160 specification which includes or
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200 W. B. Omrane, H. V. Oppens anal
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202 W. B. Omrane, H. V. Oppens of s
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204 The extrema detection method ba
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206 price 0.8565 0.8575 0.8585 0.85
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208 We distinguish three possible c
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210 originates. The most active tra
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212 Table 2 Predictability of the c
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214 6 Conclusion Using 5-min euro/d
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216 where σk is the standard devia
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218 If we meet a particular case su
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220 C.5. Triple bottom (TB) TB is c
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222 References W. B. Omrane, H. V.
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Juan M. Rodríguez-Poo · David Ver
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Semiparametric estimation for finan
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254 between price changes and durat
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256 simply aggregated. Even after a
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258 is to make use of the fact that
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260 together with the restrictions
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Table 3 Estimated probabilities of
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264 A. S. Tay, C. Ting More interes
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Table 4 Estimated probabilities of
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268 Acknowledgements Tay gratefully
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270 This paper explores the effect
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272 contrast, price responses to po
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274 Fig. 1 Continuous line is the T
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276 the β’s can form a convex sh
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278 fixing some intervals around th
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280 . That is for a given absolute
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282 30 25 20 15 10 5 CC UNEMW ISM U
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Appendix Table A1 Consumer confiden
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Table A3 Non-farm payrolls • ✓
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Table A5 Weekly unemployment claims
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290 Table A8 Retail sales • ✓ 1
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292 Table A12 GDP, BI, TB and PI Re
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294 V. Voev with the problem of how
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296 V. Voev 2.1 A sample covariance
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298 V. Voev Using the equicorrelate
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300 V. Voev where �kl(t) is the (
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302 V. Voev where hkl,k ′ l ′ i
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304 V. Voev is 1.9%. From the daily
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306 V. Voev ACF ACF ACF 0.5 0.5 0.5
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308 V. Voev autocorrelated. Indeed,
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310 V. Voev 5 Conclusion Table 2 Ro
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312 V. Voev Engle R (1982) Autoregr