NOI DUNG CHINH e Bien dong ty gia hoi doai e Mô hình độ nhạy rủi ro trao đổi tỷ giá hoi doai chau A e Phạm vi thời gian... PHƯƠNG PHÁP NGHIÊN CỨU se Sử dụng mô hình hồi quy tuyến tín
Trang 2GIỚI THIÊU
° NỘI DUNG CHÍNH
° TẠI SAO CAN PHAI THUC HIEN
NGHIEN CUU NAY
Trang 3NOI DUNG CHINH
e Bien dong ty gia hoi doai
e Mô hình độ nhạy rủi ro trao đổi tỷ giá
hoi doai chau A
e Phạm vi thời gian
Trang 4TẠI SAO CÀN PHẢI THỰC HIỆN NGHIÊN CỨU NAY
e Các yếu kém trong các nghiên cứu trước đây
se Chưa có nghiên cứu nào về đề tài này
Trang 5TONG QUAN CAC NGHIEN CUU
Trang 6PHƯƠNG PHÁP NGHIÊN CỨU
se Sử dụng mô hình hồi quy tuyến
tính
Trang 7NỘI DUNG NGHIÊN CỨU
°® Đo lường độ nhạy tỷ giá hôi đoái
° Lựa chọn mẫu của các công ty đa quốc gia
châu Á, các yêu tô kinh tế và thông kê tông
hợp
Trang 8BO LUONG DQ NHAY TY GIA
HOI DOAI
e DO nhạy biến động tỷ giá hối doai cua
doanh nghiệp có thể được đo lường
bằng mô hình thị trường gia tăng sau:
Ri, ~ Gj T bi; Kot TY; X, T Ei
Trang 9BO LUONG DQ NHAY TY GIA
Trang 10BO LUONG DQ NHAY TY GIA
Trang 11BO LUONG DQ NHAY TY GIA
HOI DOAI
e Sử dụng phương sai gần đúng - ma trần phương sai hiệp mạnh với thông
SỐ sai lệch của mật độ xác suất Li, t:
y= 4g! Bo Ag!
Trang 12LỰA CHỌN MẪU
e Các công ty đa quốc gia châu Á:
- Có văn phòng đăng ký ở Châu Á
— Hai nam liên tiếp co dữ liệu doanh thu chứng khoản
Trang 14LỰA CHỌN MẪU
e Thống kê tổng hợp: số liệu về biến động giá log hàng tuân của 5 đồng tien chau A
Trang 15
Indonesian South Korean Hong Ko Malaysian ¬ 1 ore Rupiah Wong 3 dolla Ringgit Philippine peso _.—
Mean 0.003647 0.000764 0.000014 0.000730 0.001910 0.000090 0.000988 Median 0.000970 -0.000150 0.000006 0.000000 0.000493 0.000000 0.000039 Maximum 0.384237 0.253863 0.002844 0.134524 0.104524 0.043242 0.119739 Minimum -0.202118 -0.129046 -0.002903 -0.089084 -0.096160 -0.026592 -0.085482 Std Dev 0.045538 0.019448 0.000359 0.012007 0.014216 0.006411 0.014126 Skewness 2.310513 5.756085 0.482463 1.937917 0.880054 0.692064 1.400995 Kurtosis 24.593530 §0.435100 23.128790 45.808460 21.816310 10.436920 25 482630 Nber of observations 373 522 322 322 373 322 322
Panel B : Japanese Yen Indonesian South Korean Hong Ko Malaysian ¬ 1 0re Rupia Wong dolla Ring Philippine peso naib aht Mean 0.003224 0.000856 0.000103 0.000818 0.001488 0.000182 0.000856 Median 0.000230 -0.000329 -0.001069 -0.000674 -0.000494 -0.000509 -0.000329 Maximum 0.368464 0.248556 0.079690 0.121639 0.108595 0.063151 0.248556 Minimum 0.191769 -0.134021 -0.050420 -0.083998 -0.089860 -0.033082 -0.134021 Std Dev 0.045632 0.021650 0.013364 0.016356 0.017859 0.011977 0.021650 Skewness 2.465908 3.816474 0.837442 0.953785 0.656853 0.688010 3.816474 Kurtosis 24.362430 48.689710 6.879032 12.112740 9.396104 4.961298 48.689710 Nber of observations 373 522 322 322 373 322 322
The sample penodcovers thepenod ofJanuary 13, 1993 to January $, 2003.
Trang 16KẾT QUÁ NGHIÊN CỨU
e ĐỒ nhạy rủi ro tỷ gia hoi doai cua các công ty đa quốc gia châu A
(bang III + IV + V)
e Rui ro ty gia hoi doai dai han
(bang VI)
e Cac yéu to quyét dinh độ nhạy ty
gia hoi doai Chau A (bang VII)
Trang 17Tig = 0] + BY far + Yi Me + Ei:
where 1;, the total return of firm 1 in week t, rq, designates the domestic stock market return in week
tand X, is the change in the domestic currency / U S dollar, respectively domestic currency /
Japanese Yen exchange rate ¢;, denotes the white noise error term
CGross-Secnonal Summary Staasncs
Sample Period N Mean Median Variance Maximum JAfinimum WN*(+) N*(-)
Panel A- U_S_ dollar exchange rate exposure 13/01/1993 -O8/01/2003 3634 -0.4075* -0.3472* 0.7308 4.7496 -9.4366 121 786
Trang 18Cross-sectional distribution of exchanmge rate exposures yi
countries
This table reports surremary statistics for vy, coefficients for the entire sarmple comsistimg of 3634 Asian firrr1=-
Tự = Œ + Bi ree + ¥i M+ 2:
where r, the total return of fmm im week t_ r desismates the domestic stock market returm m week
t amd ™ is the chamge m the domestic currency € U S dollar, respectively domestic cumremcy Ý Japamese Yenexchange rate 2= denotes the white noise erortenm
coefficients across
Cross-Sectional Summary Sraristics
Sample N Afean Afedian Variance Afisximum AGuaimum N*<() nO
Pao A- 0S doliay exchange rate amosure Indonesia ^s© ~0.4151* _© 5341* 0.4456 4.4068 1.9847 3 6s
oaoer aozr South Fores 216 —-0.4547* _-©O 3811* ©4=c© -3 OB^^ 1.717 3 cm:
oces ooss Hone Fonz séc _-© S5353E* _© 453©1* © <=e4~ -4 2C©C^= 2.8531 3 142
aozz oaer Malsysia 336 -0.4668* -0.3586* ©.éce^4 2.4366 1.4631 7 72
ooss oaoso Philippim==: 331 -~0.3432* _© 31€©^~* 0.5636 3.3366 4.7496 is c3
acœzz aozz Sinzz=ccze 1101 -0.36°3* 0.3128" 0.5063 3.6271 4.16°¢6 24 202
oor: oozs Thailand 622 -0.3585* ~0.321°°* © 4=scc© -3 1€^2C 2.3315 1S 170
aœz7 a-o«z Paovei B- Japaouese Yen eaxcUsaige rate amosure Indonesia 25° -O0.2S507° 0.2254" o.375°2 -1.7202 2.0115 a So7
oor oases South Fores 216 _Ầ^253 72+ _-©O 176^* 0.2646 3.3294 2.6965 7 42
ooz7 cose Hone Fonz sé© O0.3056° _-O 2128* ©O 7571 4.2630 2.9614 15 oT
oor ooces Malsysia 336 ~0.2341* -0.1357* oO.4752 3.15890 2.1802 10 62
aoœzz oaer Philippinm=: S31 -_° 2534 ~x* _-© 1530 ~* © 48O1 -3 48SéC 1.6660 31 B86
core ooze Simzeapor= 1101 0.1645 _© 1=4€@* 0.6619 —+4.291° 4.9575 ac 191
Trang 19Table V
Cross-sectional distribution of U-S
exposures of Asian firms by industries
This table reports surmrmemary statistics for yi by twenty-six mdustry groups from the folowms, regression model-
of S634 Asian iim:
Tạ — ai + Bi ree t+ Vi et Fie
where rz, the total rettemn of firmmim weekt, rr desigmatesthe cormespondmse domestic stock market retuumm m week t amd ™ is the chamge m the domestic auremncy § U.S dollar, respectwely domestc curremcy “ Japamese Yem exchange rate = demotes the white noise error temm The sarmbp.k comsists
dollar and Japanese Yen exchange rate
U.S dolla = posure Japsmes= Yor = "posure
No Industry Nw Nes Median N*O.ClUN* OO NMecsm 3) Niedian NWw*c) ¬>~*~c>
errre sanupie pertod - 01/01I/IS9S - O 2/01/2002
1 Mining f=rmine 186 —O.3s765 —O.2752 s 41 —0_.16°6 _© OE1€© 16 ac
& forestry ooes> ooszs ooze -aqzz«
2 Ceormstreaction & 333 _© =54© -© =1€©G = ss —O.23501 _-O 174 7 15 <S%-^ COmstriaction materials acqzce cos<ec oozs ooz<>
3 Food & beversz== 208 0.2416 Oo 20e°0 7 32 _c© 1€©€£ ~ _© 15364 Se 3°
oaoez= ooss= aœz7z ooess
= Textile 205 _© 41=4 _© 55—2E 2 3< —O.20°1 —O_1866 = 5<
ooeost oross facz-7e coors:
s Pape, primtine & related 1œ —0.3510 0.2842 = 534 -©O 211 -_Ầo ^5s“o 2 is
oascoz oaossz oozr: aczro
SX Peroleum reining & ss 0.6016 0.3526 o 14 0.2555 —-0.1146 3 " related imd@wetrics aœcz? œzz7z coores ocaose>
JT Chemicels & sllicd 184 _© S554 _© 453©= 1 =1 _© 535318 —O.2852 Ss = products oaeso oorse oaecoz oosss
SB Phermmsceuticsal= 3s 0.3582 —O._2767 eo 18 —O.2711 —0_1382 1 is
ooss= cores coossso corer
= Steel & primary metals 112 _© 53g&€C~^ _© 4G ~~ 2 23s 0.25290 —O.2272 = 22>
oorsz œazzzz oozss facq<cc 1© A:rtCzriCtilecz 112 -c© 444C _© 418E 3 32 0.23926 0.2020 = 23
oosss a rozœ aqzc-z coseec
11 Miechive:y & ctiritrrecriric 224 _© 5534 —O.2681 Ss 5< : — -© 2EGE4 = 2s
aœzzz œaœczz7 ooscs oasis
12 Electrical equipment 201 —O.2585 0.3406 3 42 0.2222 0.2023 3 a¢
ooss> correc caste cores 1s Computes 116 —o.s°o78 0.5150 1 15 —-O.2801 -© 1 1© 53 153
aocce orzis a ro7e az;zz
14 Niiscellam=ous os —O.3856 —O.2806 Ss 5335 _o° =4 ~€© -O21©535 Ss is mamufSctisimes industries oosir aoczz acœzzr a(qz«z
Trang 20Table V (continued
U.S dollar exposure Japanes= Yen = «posure
No Industry N Xie=m Median *Y*C=) 3+ *CO) Mem Medim N*(-) nro
Eotire sampie period - 01/01/1993 - 08/01/2003
15 Tremsport 123 -0.2803 - 2763 10 22 0.1079 -O ©OSOI 2 17
aqezz aorz« aozre oases:
16 Telecommunicstions 134 0.5428 -O 3828 5 27 0.6626 0.3569 2 35
oasos œazơc2 aœez! olriss
17 Media services 37 ~0.5343 0.4658 o & O.5687 -O.3784 1 5
œzzaz œz=ep œ11Z7 277
18 Leisure & Tourism 106 ~0.3503 -© 2104 3 17 O.2288 $= 0.1736 6 16
oosz= oops oosss oosTz
Trang 21Table Wi: U.S dollar exchange rate exposure coefficiemts y; of Asian firms by industries: Intervalmegd results using overlapping observations
This table reports cross-sectionalmeanwahires and standard devintons for vz, by twenty imadustry sroups._ estrmatedby the folowime resressionmodel-
Keer = Gir + Bir Feet + Vit Mest + He ot
where rer reports the total retum of firm i form week tto t-T_ ret desismates the domestic stock market retum from week tto t-T amd ™-—- is the domestic auremcy ẽ US dollar exchange rate HPRomweekttot-T_where T equals 1_4_12 amd 54 weeks =.—71s the whrte noise ermortenm
Crocs- Crocs- Crocs- Crocs-
No Industry Nw s=ctiomal N* s=ctiomal N* sectiomal N* sectiomal N*
mean mean mean mean
l NGimime feminge 186 o5^¬-^ s ©5~<5 7 Ầs:2aoé 35 o.8662 3°
& focesrry ooze ooze oozss corse
—O.6S557 41 oO 3506 oT -1_0130 S3 -1.6032 ©1 oaoeo> oasco oosrts o@2222
2 Ceormstroaction 333 0.4202 a 0.s026 22 o.7194 $30 12217 35
& comstraction meaterrisai= oorzre ocoz<<e oases r oasrc
—O.7S572 ©3 —o.2°54 167 -1.2411 205 -1_6047 225 ooze faczcc ooszz ooss=
Ss Food & beveorsz=: 208 o.3s8235 “7 ©5~== 3 O.s276 25 1.03540 3°
facœzzz oozss oaers > ooriz 0.4936 34 0.67352 se _© 84*€© 100 -1.4100 117 oot z< oaoerzs faœzz7z oasso
= Teectile= 205 o.3s3s62 2 o.44580 16 Oo.s720 21 1.2322 3°92
fœczzz oaes > cosis f{ rrzc
—O.6328 4€ _ cSẰ~TOGœ ss _-ÐO 8€©3 107 -1 28 7© 111 -a-«zr ooaso: ooszs oor
S Pepe, printinse & related l1lœ © 5©S84 1¬ © 54ts€ cơ © 5S€£4 se o.7o0So 10
aœzzz aœzzz cosce ooss:
—O.6250 24 O.773s0 4E -1.0086 62 -1.4061 7s oaer>> oosrs oorssr {azzrz£t
« Petroleum reinine = =8 ©1li6Ằ2= ° ©=s5ac=- = o.3s025 = ©4c©-~- Ss related indwsetrics aœrra faœ7zz« ooer> oosir
—O.53010 14 _© S1© 22 -1_1700 37 -1.6282 3° ooss> oasis oroccs f rrze
JT Chemicals & related 184 o.2705 1 o.4=665 cơ © 753 71 1s o.2550 24 indwstics faoarczr oozs= fœœerz aœ7z7
-© 7OCE1 =1 Oo 7220 ss —O.8B8580 101 -1.3585 118 oaes> oosco x faœ7re
S Pharmmscectical= ss o2zIs= ° o.2°12 53 o.4150 © 2.0002 10
f{aœzzz7 corse cosets fzr-c _© ==©= 18 —O.6806 37 —O.711° 45 -1 153 1 42
Trang 22Cross- Cross- Cross- Cross-
No Industry Nw sectiomal N* sectiomal N* sectiomal N* sectiomal N*
mean mean mean mean
SS Stel & primey metals 112 o.4761 2 0.5272 7 0.6655 12 1.7954 13
coos: coras oorrse faz«zc 0.6378 25 —O.8756 “53 O.S9700 66 -1.4066 62 coer ooss> aœzz= -czzzo 1© AtrtCczrictilez 112 © 4séc 3 o.4195 7 o.654-4 11 1.1325 21
oosecost ooess oorrr ouizre 0.62335 32 —-O.83387 s2 -1.06s-= c+ -1.489°6 3° oaes> ocosss oose> a rra=œ
11 Miechimey & emzimearine 224 © 4cs4 Se oO.68835S 14 O.8158 335 1.73192 s5
oozs> ooes> ooasor œazz2z2 0.73335 36 0.9322 S1 -1.04°1 S44 -1.5485 so cooee> aœzzz aœ<z7 a roœc
12 Hlectrical squipment 201 0.6068 3 o.sseo- 11 115384 37 1.1930 44
z«« ooss> oosss cores 0.6463 42 O.8116 86 —-o0.°645 837 -1.2588 89° oozso oaer> costes oose>
153 Computers 116 O.Ss866 1 © 7271 1 G CSC^21 1S 2.860< 4C
errt aozzo oosi«<e omz:
-1.10°86 15 -1.0062 29 -1.16535 29° -1.5335 29° oorss oorss oors> œz7z2
14 *iizcelizrect:z os 0.2515 < o.25835 3 © =5é© = ©C1iC4 1C smmamuftfactirinme imdustrics -acozcc cooz<co oorost f{azzz«
0.6222 25 —-0.6673 3€ O.9668 s2 -1.3368 356 ooszz oosrs oose: ori 1S Tremsport 1235 0.4508 Ss o.4584 12 o.7478 22 11-2833 32
corse oozsr> oasis O2232 -0.65°4 22 —O.8103 4€ -O.S862 — -1.540°2 61 coors ooss> cores œa razc 1€ Tele icati 154 © 54GC1 Ss o.43s77 14 o.6304¢ 21 1.66925 534
oozsz ocozzs oosor f{a;zzz cap 27 —O.92652 48 CO SẴSC€C so -1.2424 4€ coors oors> oorrs coors:
17 Niedis s=rvice= 37 0.3260 ° 0.28635 3 © csc4 Ss 1 €Ẵ4S3 11
cosz< ooss> O227= o 222s 0.6622 sS —-O0.7208 sS —O.S8282° 11 -1 54SE 1© olros: ores oleic azzr-o
18 Leswre & Tourism 106 O.2717 3 © 541€ ° 0.6502 18 1.2987 31
core ooze corre Guisi«e
—-©.612935 17 -O.72S5= 3€ -1 1652 4€ -1.73547 s7 oosss caste oorr: orer=
Trang 23Sample leek 4wee ks 12 weeks 354 weeks
Crocs- Crocs- Crocs- Crocs-
No Industry Nw sectiomal N* sectiomal N* sectiomal N* sectiomal N*
mesn mesn mesn mesn
12 Utilitics 3° O.3s612 3 0.4374 15 0.6550 16 1.0117 18
oaersso aœ«r? aozrcz azrez -©O SSO1 Ss 0.6021 sS _c© 6Ằ&4^8 $s -1.3026 3 oreo ozos> ooss: o tre
20 Utility s=mices 37 ©5347 —~ 1 © 5EO1 53 4ce44 5 1.0864 12
aozena aœ<zo oor 2222 _ 4854 6 0.6284 14 —-O.2622 17 -1.5400 16 corre a;⁄œr azzzo œ2zz+
21 Retail 105 0.4542 o o.42028 sS ©OS€Ẵ21 1€ 1.32635 1€
“acœ«ez aœzzz facecz œa z2z
©O.5366 22 —O.75135 4E 0.2226 48 -1.4172° co oaezo ocosz« aozez a;z«z
22 Beamk=: 328 0.2455 3 0.3295 7 o.so72 22 o.7148 42
ools> aœzzz aœzzz aoz«r -O.S882 71 —-0.7443 148 0.8902 156 08.9268 174 acgzcc ooes> ocoere oaoees
233 Imewrenc= T4 © 5531€ 2 0.4766 eo © -¬cc Ss o.o460 14
oaerse ooss= œ roœe {a;z,«
-O 5312 —~ 3 O.s642 26 —-O.786°2 3s -1.0842 3° acœzzo aorco« a ra&z a;zzz
24 Resl Estst= 240 oO.3221 cơ 0.34352 7 5= € 15 0.6702 24
oolmre ooze aœzze -a-«zct
—-oO.7e°4 81 —-0.2854 118 -1.3967 134 -1 ©5353 167 aœzzz aozoz oass> oO2227=
25 Othe 61 O.3725 3 0.5010 7 o.s745 12 1.1733 10
oaer> oases ao<zo œazzzez _© 4= ~œ > —-O.5412 235 O.7278 25 -1.2977 30 oaoess oaoeis aœzzz7 azzoz
26 Diversified end oth 123 0.2782 1 0.3850 1 0.4080 12 O.s868 16 industrials ooze: oozz= oozss acozzo
O.773s0 25 -1_163° 70 -1.3441 75 -1.8258 75 -aoe«ro oosss o202= a;«zz Across all ind wustries 3634 0.3324 735 0.4633 133 0650S A427 12S17 645