[nh] detai ueh500 2012

i

MC LC

DANH MC CC T VIT TT ............................................................................................. iv

DANH MC BNG BIU .......................................................................................................... v

DANH MC HNH ..................................................................................................................... vi

LI M U ............................................................................................................................... 1

1. L DO CHN TI ........................................................................................................ 1

2. MC TIU NGHIN CU ................................................................................................. 2

3. PHNG PHP NGHIN CU ........................................................................................ 2

4. NI DUNG NGHIN CU ................................................................................................. 3

5. NGHA NGHIN CU CNG TRNH .......................................................................... 4

6. HNG PHT TRIN TI .......................................................................................... 5

1. GII THIU ............................................................................................................................ 6

2. TNG QUAN CC NGHIN CU ...................................................................................... 6

3. KHUNG L THUYT C S V M HNH VALUE AT RISK ...................................... 12

3.1 Khi nim gi tr ti ri ro ................................................................................................ 12

3.2 Cc m hnh tnh VaR ...................................................................................................... 14

3.3 D bo phng sai : .......................................................................................................... 16

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3.3.1 M hnh tham s : ..................................................................................................... 16

3.3.2 M hnh phi tham s ................................................................................................. 18

3.4 Backtesting VaRs .............................................................................................................. 19

3.4.1 Kim nh Unconditional Coverage ......................................................................... 20

3.4.2 Kim nh tnh c lp ............................................................................................. 21

3.4.3 Kim nh Conditional Coverage ............................................................................. 23

4. P DNG M HNH VALUE AT RISK LNG HA RI RO T GI TRONG

KINH DOANH NGOI HI ..................................................................................................... 24

4.1 Khung l thuyt c s v vn ri ro trong kinh doanh ngoi hi ................................. 24

4.1.1 c im ca kinh doanh ngoi hi trn th trng forex: ...................................... 24

4.1.2 Cc loi ri ro nguyn nhn pht sinh ri ro trong giao dch kinh doanh ngoi

hi..25

4.1.3 Vn trng thi ngoi hi (exchange position) ...................................................... 27

4.1.4 Vn qun tr ri ro trong kinh doanh ngoi hi ................................................... 28

4.2 D liu v xy dng m hnh thc nghim ...................................................................... 29

5. KT QU THC NGHIM : .............................................................................................. 30

5.1 Kt qu xc nh VaR cho tng cp tin t ring l: ........................................................ 30

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5.2 Xc nh hn mc u t, li nhun v thua l tch ly ca danh mc da vo gi tr

VaR ....................................................................................................................................... 32

5.3 Kim tra m hnh Backtesting VaRs .............................................................................. 34

5.4 Xc nh VaR cho c danh mc...................................................................................... 39

5. KT LUN ......................................................................................................................... 41

DANH MC TI LIU THAM KHO .................................................................................... a

PH LC .................................................................................................................................... d

iv

DANH MC CC T VIT TT

ADF Augmented Dickey-Fuller test

GARCH T hi quy phng sai thay i c iu

kin tng qut

HS Historical Simulation model

P/L Profit/loss distribution

TSSL T sut sinh li

VaR Value at risk

VAR-COVAR Ma trn phng sai- hip phng sai

EVT Extreme Value Theory

v

DANH MC BNG BIU

Bng 2.1: Tng hp cc m hnh VaR truyn thng

Bng 3.1: Tng hp cc phng php tnh VaR ph bin

Bng 4.1: Tng hp cc giao dch lm pht sinh trng thi ngoi hi

Bng 4.2: Thng k m t thu nhp ca cc cp tin t trong giai on 1/11/2006-1/11/2012

Bng 4.3: Kim nh ADF test v tnh dng ca cc bin

Bng 4.4: Kt qu o lng bin ng ca cc cp t gi bng m hnh GARCH (1,1)

Bng 5.1: Kt qu tnh VaR cho tng cp tin t (n v %)

Bng 5.2: Kt qu tnh VaR cho tng cp tin t ring l (n v USD)

Bng 5.3: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t GBP/USD

Bng 5.4: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t EUR/USD

Bng 5.5: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t CAD/USD

Bng 5.6: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t AUD/USD

Bng 5.7: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t CHF/USD

Bng 5.8: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t NZD/USD

Bng 5.9: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t JPY/USD

Bng 5.10: Ma trn phng sai ca cc bin

Bng 5.11: Ma trn tng quan gia cc bin

Bng 5.12: Kt qu tnh VaR cho ton danh mc

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DANH MC HNH

Hnh 3.1: Xc nh gi tr VaR t th phn phi xc sut ca chui thu nhp

Hnh 4.1: Biu phn phi tn sut ca cc cp tin t

Hnh 4.2: Bin ng t gi hng ngy ca cc cp tin t

Hnh 5.1: Kt qu d bo VaR cho tng cp tin t ring l

Hnh 5.2: Kt qu P/L tch ly hng ngy ca tng cp tin t

1

LI M U

1. L DO CHN TI

Forex l mt th trng u t y tim nng nhng li cha ng ri ro cao thng qua

bin giao ng ln ca cc mc gi v nhng lc n by. S xut hin ca nhn t

ri ro t ra nhu cu cp thit cho cc ch th tham gia th trng l: Cn phi c

mt cng c lng ha nhng nh hng ca ri ro, kim sot v phn b chng

mt cch hp l nhm t c mc tiu li nhun trong iu kin th trng lun bin

ng khng ngng. gii quyt vn ny, hng lot cc m hnh ton hc phc tp

vi s kt hp ca cc l thuyt v xc sut, ti u ha v c lng ra i. Trong

, gii ti chnh hin i c bit ch ti m hnh Gi tr ti ri ro (VaR), v y

cng l m hnh c ng dng rng ri trong qun tr ri ro ti cc ngn hng ln trn

th gii nh Goldman Sachs, J.P. MorganTuy nhin, tri qua hn mt thp k hnh

thnh v pht trin m hnh ny cng bc l mt s thiu st nht nh v bn thn

VaR, tuy l mt cng c qun tr ri ro tt nhng hiu qu s dng li chu tc ng rt

ln bi mc ch, trnh hiu bit cng nh kinh nghim ca ngi s dng. Chnh v

vy m vn t ra y l: VaR l g v s nguy him nh th no nu khng hiu

v s dng ng chc nng ca n? M hnh VaR no c kh nng d bo ri ro mt

cch chnh xc? u l nhng sai lm thng gp khi s dng VaR ? VaR c p

dng ra sao trong vic phng nga nhng ri ro pht sinh trong qu trnh kinh doanh

ngoi hi? Xut pht t nhng nhu cu ny, bi nghin cu tin hnh ng dng m

hnh Value at risk trong lng ha ri ro kinh doanh ngoi hi trn th trng forex,

thng qua nhm to c s khoa hc cho vic ra quyt nh, phn b danh mc u

t, hn ch n mc thp nht nhng nh hng xu do ri ro gy ra. T gp phn

nng cao hiu qu ca nghip v kinh doanh ngoi hi ti h thng cc ngn hng

thng mi Vit Nam.

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2. MC TIU NGHIN CU

V mt nh tnh, ti tp trung nghin cu cc l thuyt v hot ng kinh doanh

ngoi hi trn th trng Forex. Nhng im c th ca th trng ny, cc loi ri

ro pht sinh trong giao dch kinh doanh ngoi hi. Vn v trng thi ngoi hi,

xc nh v duy tr mc trng thi ngoi hi hp l. Phn tch nguyn nhn pht sinh

ri ro v cc vn ch yu trong qun tr ri ro kinh doanh ngoi hi

V mt nh lng, ti tin hnh ng dng m hnh value at risk vo vic lng

ha ri ro trong kinh doanh ngoi hi. T kt qu thc nghim, ti tp trung lm

r mt s vn sau:

Quy trnh thc nghim ng dng VaR trong o lng ri ro t gi l g ?

Lm th no lng ha chnh xc nhng bin ng ca d liu ti chnh

(chui t gi) vi 2 c th c bn ca chng l bin ng theo nhm v hin

tng fat tail ?

Gi tr VaR c s dng ra sao trong thc tin u t c th l vic xc

nh hn mc u t ti a v li nhun/thua l (P/L) tch ly d kin

Vn xy dng tiu chun kim nh la chn m hnh VaR thch hp

vi chui d liu nghin cu

3. PHNG PHP NGHIN CU

Phng php nghin cu ca ti c th c chia lm phn :

- i vi nhng mc tiu nh tnh, bi nghin cu ch yu s dng phng php

thng k, m t, so snh, phn tch v tng hp vi mc ch trnh by nhng

vn l thuyt nh: cc c im c trng ca th trng ngoi hi, vic xc

nh v duy tr mt trng thi ngoi hi hp l, nhng li ch v ri ro no

thng pht sinh trong qu trnh kinh doanh ngoi hi.

- i vi vic nh lng, bi nghin cu s dng m hnh gi tr ti ri ro

(Value at risk) : (1) lng ha nhng bin ng t gi qua cch tip cn tham

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s (m hnh riskmetrics, GARCH (1,1)) v phi tham s ( m hnh Historical

Simulation), (2) o lng cc khon l tim nng thng qua gi tr VaR v (3)

xc nh cc mc li nhun/ thua l tch ly (P/L) theo thi gian v hn mc

u t ti a cho tng cp tin t ring r cng nh cho ton danh mc. V cui

cng l vn kim nh tnh thch hp ca m hnh qua xy dng php th

Backtesting VaRs

4. NI DUNG NGHIN CU

ti tp trung vo 3 ni dung nghin cu sau :

Th nht l tng quan v hot ng kinh doanh ngoi hi trn th trng forex ca cc

ngn hng thng mi. Phn tch cc c im c trng ca th trng ny t

rt ra c cc tng kt v nhng li ch v ri ro s pht sinh khi tham gia vo th

trng ny:

- Tng quan v cc giao dch kinh doanh ngoi hi

- Li ch ca kinh doanh ngoi hi trn Forex

- Trng thi ngoi hi

- Vn qun tr ri ro trong kinh doanh ngoi hi

Th hai l

- Tng quan cc nghin cu v m hnh Value at risk

- Khung l thuyt c s v m hnh Value at risk

- Cc phng php tnh VaR

- Vn d bo phng sai : Cc m hnh tham s ( RiskMetric, GARCH(1,1))

v phi tham s (Historical Simulation Model)

- Kim tra mc ph hp ca m hnh qua php th Backtesting

Th ba l xy dng m hnh v kt qu thc nghim

- La chn h thng bin chui thi gian d liu, xy dng m hnh

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- D Bo VaR cho tng cp tin t ring l v cho c danh mc. T phn tch

tc ng ca vic a dng ha u t trong gim thiu ri ro ton danh mc

- Xc nh hn mc u t, li nhun v thua l tch ly ca danh mc da vo

gi tr VaR

- Kim nh mc ph hp ca cc m hnh VaR xy dng bng vic s

dng php th Backtesting

- Kt lun v cc xut lu khi p dng m hnh VaR trong qu trnh qun tr

ri ro kinh doanh ngoi hi

5. NGHA NGHIN CU CNG TRNH

Ba ng gp quan trng ca ti l :

- V mt l lun, ti h thng c mt s nghin cu v vn lng ha

ri ro cho chui d liu ti chnh, cc vn pht sinh v cc hng nghin cu

mi, ch ra c 2 im c th ca phn phi d liu ti chnh l bin ng

theo nhm v hin tng fat tail, cng cc khung l thuyt c s, cc m hnh

gii quyt ang c p dng v tip tc nghin cu pht trin. i vi i

tng nghin cu l ri ro t gi, ti cng khi qut c cc im chnh

trong qun tr ri ro t gi nh cung cp mt ci nhn h thng v ri ro t gi,

nguyn nhn pht sinh, cc yu t nh hng, vn xc nh v duy tr trng

thi ngoi hi hp l v cc nn tng c s trong qun tr ri ro kinh doanh ngoi

hi.

- V mt thc tin, ti tin hnh xy dng mt m hnh lng ha cc bin

ng t gi, o lng cc khong l tim nng v xc nh hn mc u t

thng qua gi tr VaR. ng thi cng a ra c cc tiu chun kim nh

la chn m hnh VaR thch hp cho danh mc u t. T hn ch n mc

thp nht nhng nh hng xu do ri ro gy ra v gp phn nng cao hiu qu

ca nghip v kinh doanh ngoi hi ti h thng cc ngn hng thng mi Vit

Nam.

5

- Ngoi ra, ti cn cung cp c s l thuyt v phng php lun cho cc

nghin cu tip theo Vit Nam. ng thi n cng cung cp thm mt tnh

hung nghin cu cho cc mn hc nh: Thanh ton quc t, Qun tr ri ro,

Kinh t lng ng dng v phng php nghin cu.

6. HNG PHT TRIN TI

ti c th m rng theo hng, o lng cc gi tr vt mc cho nhng s kin

Black swan thng qua cch tip cn l thuyt gi tr vt mc Extreme Value Theory

(EVT). S dng phn b Pareto xc nh t trng danh mc ti u v xc nh phn

phi cho ton b danh mc thng qua hm copula of portfolio

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1. GII THIU

L th trng ton cu vi khi lng giao dch khng l cng s ng o v a dng

ca s lng thnh phn tham gia. Forex c xem l mt mi trng u t y ha

hn. Song, cng vi kh nng kim li ln th mc ri ro m nh u t phi gnh

chu cng tng theo do tc ng n t 2 yu t c th chnh ca th trng ny l: bin

dao ng gi ln v lc n by mnh. Ri ro y c xem l nhng bin ng

ngoi k vng. iu c ngha l, n l mt c tnh gn vi th trng, chng ta

khng th loi b n m ch c th hn ch n mc thp nht nhng nh hng xu do

n gy ra thng qua lng ha cc bt trc bng cng c xc sut. T nhu cu ny

thc y cc nh nghin cu v gii thc t kho st, xut v pht trin nhng m

hnh qun tr ri ro thch hp. Qun tr ri ro trn c s nhng m hnh Value-at-Risk

(VaR - gi tr chu ri ro) nhanh chng tr thnh mt ch hc thut nng v nhn

c s quan tm c bit ca nhiu nh u t cng nh cc t chc ti chnh ln. Tuy

nhin, tri qua hn mt thp k hnh thnh v pht trin VaR cng bc l nhng thiu

st nht nh. Trong 2 vn ng ch nht l: (1) VaR hu nh ch c kho st

trong iu kin th trng n nh. iu ny t ra cu hi: Liu rng VaR c cn duy

tr c mc d bo chnh xc trong iu kin th trng c s dao ng mnh di

s tc ng ca nhng s kin black swan ang xut hin ngy mt nhiu ? (2) Vic

o lng VaR truyn thng thng phi da vo nhng gi nh phn phi chun ca

chui d liu. Song, nhng kho st thc t cho thy, y l mt gi nh phi thc t v

cc chui d liu t ga thng c hin tng fat tail tc l nhng kh nng mt vn

ln tp trung nhiu pha ui ca th phn phi. Vy th gii nghin cu ti chnh

c nhng hng gii quyt nh th no i vi vn ny? Nhm i tm li gii cho

nhng cu hi t ra, bi nghin cu tin hnh phn tch v tng hp t cc khung l

thuyt c s v m hnh VaR cng nh vn qun tr ri ro kinh doanh ngoi hi, kt

hp vi hng lot cc nghin cu thc nghim trong sut nhng bc pht trin ca lnh

vc lng ha ri ro a ra c c th ca cc ri ro t gi pht sinh. Quy trnh p

dng VaR trong lng ha ri ro kinh doanh ngoi hi v nhng iu cn lu khi p

dng VaR trong thc tin u t. ng thi, hng n nhng mc tiu nh lng, bi

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nghin cu cng tin hnh xy dng m hnh VaR cho danh mc tin t gm 7 ng

tin c doanh s giao dch ln nht trn th trng Forex. Bin ng s c o lng

thng qua c 2 cch tip cn l tham s v phi tham s. Vn la chn khung thi gian

v tin cy s c kim nh qua php th Backtesting VaRs. Cui cng, gi tr VaR

s c nghin cu trong 2 trng hp l vi tng cp t gi ring l v vi ton b

danh mc u t. Vic phn tch s c tin hnh lm r li ch thu c t vic a

dng ha u t.

2. TNG QUAN CC NGHIN CU

Hng lot cc cng trnh nghin cu tp trung vo vn m hnh ha ri ro th

trng, trong hu ht u da vo cch tip cn m hnh gi tr ti ri ro VAR.

Nghin cu ca Hendricks (1996) tin hnh phn tch 12 m hnh VAR khc nhau khi

tnh ton da trn chui d liu qu kh cho thu nhp t gi (exchange rate returns) v

tm thy rng phng php m phng qu kh (historical simulation) cho kt qu tt

hn mc 95% so vi 99% hoc tin cy cao hn v phng php trung bnh trt

c trng s ly tha cho kt qu ng tin cy hn khi s dng nhn t phn r bng 4

i vi chui d liu hng ngy.

Barone-Adesi and Giannopoulos (2000) kim nh phng php m phng qu kh

cho chui thi gian t 1/1997- 12/1999 vi danh mc u t S&P 100 bao gm c cc

quyn chn . H kt lun rng c th xc nh VAR bng c 2 cch l s dng phng

php phng sai hip phng sai hoc k thut m phng qu kh. Vic s dng phng

php thng k v c im ca ti sn ti chnh s nh hng n tin cy ca gi tr

VaR c tnh. Hendricks (1996) trong nghin cu ca mnh chn ngu nhin 1000

danh mc quyn chn tin t kim nh tnh hiu qu ca m hnh VAR . Mc tiu

ca nghin cu ny l chng minh v so snh s ging nhau gia ri ro o lng bng

VAR v ri ro thc t pht sinh. ng tin hnh o lng ri ro th trng vi 3 phng

php c bn : (1) trung bnh trt, (2) trung bnh trt c trng s ly tha v (3)

phng php m phng qu kh. Da vo tng phng php cp trn cho ra cc

kt qu VAR khc nhau v ng vn cha th i n kt lun v mt phng php o

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lng VAR ti u. Trong kim nh ny ng cng ch ra rng vic la chn tin cy

khc nhau cng c nh hng ln n kt qu VAR o lng c. Nghin cu ca

Vlaar (1998) tin hnh chn mu 25 danh mc u t khc nhau cha tri phiu chnh

ph H Lan k hn 12 nm v 8 nm tin hnh o lng vi 3 m hnh VAR khc

nhau (bnh qun qu kh, Monte Carlo v phng sai hip phng sai). ng thi, da

trn tin cy l 99% v thi gian d liu l 10 ngy. Kt qu cho thy : mt l, phng

php bnh qun qu kh ch cho kt qu tt khi v ch khi thu thp c mu d liu

ln. Hai l, Monte Carlo i hi cn thc hin php lp nhiu c th xc nh VaR

chnh xc. Ba l, da vo gi nh phn phi chun v m hnh phng sai thay i theo

thi gian, khi kt hp Monte Carlo v phng php phng sai hip phng sai cho

kt qu tt hn so vi cc trng hp cn li .

Nghin cu ca Duffie and Pan (1997) a ra ci nhn tng quan c s l thuyt ca cc

m hnh VaR c s dng trong lng ha ri ro th trng, kha cnh kinh t lng

cng nh nhng ng dng thc t ca n. Jorion (2001) a ra mt nghin cu hon

chnh v chi tit v gi tr ti ri ro, vic p dng n i vi nhng loi ri ro v danh

mc u t khc nhau. Ngoi ra, ng cng ch ra nhng by thng gp i vi cc m

hnh ny. Engel and Gizycki (1999) pht trin nhng nghin cu ca Hendricks v

xut nhng kim nh mi v chnh xc v tnh hiu qu ca m hnh VaR thit lp.

Trong mt nghin cu khc, Rockafellar and Uryasev (2002) tip cn theo hng gi

tr ti ri ro c iu kin nh l mt phng php o lng v gii quyt nhng thiu st

trong cch tnh VAR truyn thng, ch yu l vn thiu tnh cht ch v gii hn

thng tin cung cp bi VAR (VAR khng th cho bit nhng khon l qu mc vt

ngng gii hn nht nh). ng thi, h cng ra c phng php ti u ha cch

o lng VaR c iu kin CVaR. Kt qu t Cng trnh ca Alexander (2001) cung

cp mt ci nhn ton din v cc m hnh lng ha ri ro th trng, ng thi ng

cng a ra nhng v d in hnh v cch p dng chng trong thc t bng cc phn

mm khc nhau. Cch tip cn VaR ca Kaplanski and Levy (2009) li ch yu tp

trung vo vic nhng qui nh hin thi cho php s dng cc m hnh qun l ri ro

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ni b. iu ny dn n cc ngn hng thng mi hot ng vi mt mc ri ro vt

ngng v bp mo cu trc phn b vn ca mnh.

Phng php o lng VAR chun thng c tin hnh da trn cc gi nh v s

phn b xc sut. Mt trong nhng gi nh ph bin nht l gi nh rng chui d liu

chy VAR c phn phi chun. Gi nh phn phi chun p t mt vi gii hn ln

cc hm phn phi li nhun nh v tnh cn xng v quan trng hn l khng tnh n

cc nhn qu mc trong th phn phi. Tuy nhin, nhiu cng trnh nghin cu

nh Mandelbrot (1963), Fama (1963), Mussa (1979), Andersen et al. (1999) and

Manganelli and Engle (2001) ch ra rng nhng gi thit ny l gn nh phi thc t.

Theo nh kt qu nghin cu ca Hols and De Vries (1991), Huisman et al. (1997),

Huisman et al. (1998), Wagner and Marsh (2003) th nhng chui d liu ti chnh

thng c hin tng ui dy (fat tail). Hn th na chng cn chu nhng s bin

ng theo nhm (volatility clustering). iu ny hm rng mc d cc d liu th v

li nhun c th khng tng quan nhng li nhun bnh phng hoc li nhun tuyt

i s c hin tng t tng quan dng. gii quyt nhng kha cnh ny, mt vi

cch tip cn VAR thay th c s dng, nh l phn phi Student-t, m hnh

ARCH/GARCH c xut bi Engle (1982) and Bollerslev (1986), hoc chun hn

hp cng l mt phng php c thc hin trong nghin cu ca Duffie and Pan

(1997).

Nghin cu ca Simons (1996) nh ngha ri ro tng ng vi cc ti sn ti

chnh v ch ra 2 gii hn lin quan n VaR : th nht, VaR ch quan tm n 1

im trong th phn phi li nhun v thua l. Tuy nhin, iu cn thit l phi c

mt i din cho tt c cc phn phi trong hm. Th hai, VaR t ra kh yu khi o

lng chnh xc ri ro trong nhng iu kin th trng vt mc.

gii quyt vn ny, nhiu tc gi nh hng cc nghin cu ca h theo cch

tip cn l thuyt gi tr vt mc Extreme Value Theory (EVT). Vic o lng bng

EVT cho kt qu mnh khi p dng i vi cc lnh vc nh bo him v qun tr ri ro

ti chnh. Nghin cu ca Embrechts, Kluppelberg and Mikosch (1997) cng s dng

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cng c EVT nh gi hin tng fat tail vi cc chui d liu thi gian khc nhau.

Tng t , cc nghin cu ca Resnick (2007). McNeil (1997a, 1997b, 1998, 1999),

tp trung vo phng php POT bng cch s dng phn b Pareto tng qut o

lng nhng ngng bin ng vt mc. POT cng l phng php c s dng

trong cc nghin cu ca Matthys and Beirlant (2000), Blum and Dacorogna (2002),

Wagner and Marsh (2003).Trong , h so snh vic s dng phn phi t- student vi

cc m hnh o lng s bin ng GARCH-t. Nghin cu ca Brooks et al. (2003)

s dng phn b Pareto tng qut cho cc hp ng tng lai, Gonzalo and Olmo (2004)

s dng phng php m phng qu kh xc nh ngng ti u. Block Maxima l

phng php c s dng trong cc nghin cu Caserta and De Vries (2003). H tin

hnh phn ha cc phn tch ca mnh cho trng hp ti a v ti thiu ca ch s

AEX. Cng trnh ca Cotter and Dowd (2007) th s dng phng php ny ro snh

cc ri ro v pha ui i vi cc lnh gii hn v lnh th trng trong hm phn phi

li nhun kinh doanh ngoi hi. Robert, Segers and Ferro (2008) phn tch hin tng

fat tail cho d liu li nhun t ch s FTSE 100. Rt nhiu trong s cc nghin cu

ny v c nhng nghin cu khc s dng vic xc nh gi tr ti ri ro thit lp

khung EVT. Mt kt lun chung c rt ra t cc nghin cu l EVT l mt phng

php t ra kh hiu v c pht huy tnh ti u khi tin hnh o lng cc hng bin

ng vt mc trong chui d liu.

Bng 2.1 Tng hp cc m hnh VaR

Ngun :Extrem risk management, Christina Ray, The McGraw-Hill Companies, Inc

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Mc d VaR c cho l mt cng c hu ch nhm o lng ri ro th trng ca cc

danh mc u t, cc gii hn v thiu st t m hnh vn ang l vn gy nhiu

tranh ci . Nghin cu ca Dowd (1998) ch ra 3 gii hn chnh ca phng php tnh

VaR:

- Th nht, m hnh ny s dng d liu qu kh d bo cc hnh vi trong tng

lai

- Th hai, m hnh c xy dng da trn cc gi nh khng phi lun thch hp

trong tt c cc iu kin. V vy, ngi dng cn ht sc cn trng i vi nhng

gii hn ca m hnh v xc nh hm cho cc tnh ton ca mnh.

- Th ba, gi tr VaR d bo ch c th c s dng ra quyt nh ng khi

ngi dng c kin thc v khi nim gi tr ti ri ro cng nh qu trnh xy dng

m hnh

C v nh VaR l mt phng php c th c dng cho nhiu mc ch khc nhau :

nh gi ri ro, gii hn ri ro, thit lp cc ngng an ton vn, phn b vn ni b.

Tuy nhin, VaR vn cha phi l cu tr li hon ho cho cc thch thc t ra trong

qu trnh qun tr ri ro. Khng c mt l thuyt no tn ti chng mnh rng VaR l

cch o lng xp x m da vo n ta c th thit lp nhng quy tc ra quyt nh ti

u. VaR khng gip ta o lng c nhng s kin ri ro (nht l khi c khng hong

ti chnh hoc mt s v th trng) v vy cn c nhng kim nh stress tests b

tr thm, song song vi vic xc nh VaR. Th nht, v VaR khng th tnh n mc

thanh khon khc nhau gia cc cng c ti chnh nn cc gii hn v k hn v quyn

chn vn rt cn thit. Th hai, v VaR khng o lng ht cc thng tin th trng c

lin quan nn n ch c th l cng c tt khi c s dng bi cc nh qun tr ri ro c

kinh nghim. Tuy vy, VaR l mt cng c o lng ri ro mang nhiu ha hn, nht l

khi n l tm im m ra thi k nghin cu v pht trin mi trong lnh vc lng ha

v qun tr ri ro

12

3. KHUNG L THUYT C S V M HNH VALUE AT RISK

3.1 Khi nim gi tr ti ri ro

VaR thng c nh ngha l khon l tim nng ti a ca mt danh mc hoc mt

ti sn qua mt khon thi gian v mt xc sut nh trc khi xy ra cc chuyn hng

ngoi mong i ln tng i ca cc bin th trng nh (gi c, li sut, t gi).

Var thng c xc nh theo n v Dollar $VaR. Trong :

Pr ($ thua l > $ Var) = p

S c (1-p) *100% ln khon l s nh hn gi tr VAR

xy dng m hnh cho log thu nhp, vic xc nh Var s da vo hm sau:

Pr (-RPF > VAR) = p

Pr ( RPF < - VAR ) = p

V vy VAR c nh ngha l con s m ta s nhn c khon log thu nhp t nht

vi xc sut p. iu ny hm rng chng ta c (1-p)*100% tin cy rng mc thu

nhp thu c s ln hn VAR.

$VaR = VPF (1- exp (-VaR))

Gi

l p.100% VaR cho thu nhp 1 ngy k tip v gi nh rng thu nhp c

phn phi chun vi trung bnh = 0 v lch chun l PF,t+1. Ta c :

Pr (RPF, t+1 < - VaRp

t+1) = p

Pr (RPF, t+1/ PF,t+1 < - VaRp

t+1/ PF,t+1) = p

Pr (zt+1 < - VaRp

t+1/ PF,t+1) = p

(- VaRpt+1/ PF,t+1) = p

Vi (*) l hm mt tch ly ca phn phi chun

- VaRp

t+1/ PF,t+1 = -1

(p)

VaRp

t+1 = -PF,t+1 -1

p

13

Nu chn p = 0.01 ta c -1p = -1

0.01 = -2.33 v gi s lch chun d bo cho thu

nhp vo ngy mai l 2.5% ta c :

VaRp

t+1 = -PF,t+1 -1

p = -0.025(-2.33) = 0.05825

Kt qu ny c ngha l c 1% xc sut cho vic khon l ngy mai s vt mc 5.825%

gi tr danh mc ngy hm nay. Nu gi tr danh mc ngy hm nay l 2 triu dollar th

$ Var s l :

$VaR = VPF (1- exp (-VaR)) = 2000000 (1- exp (-0.05825)) = $ 113172

Hnh 3.1: Xc nh gi tr VaR t th phn phi xc sut ca chui thu nhp

Ngun : Elements of nancial risk management / Peter Christoffersen.2nd Edition

14

3.2 Cc m hnh tnh VaR

tnh gi tr VaR, hin ti c kh nhiu m hnh khc nhau c s dng, trong

ph bin nht l 3 m hnh sau:

Mt l, m hnh m phng qu kh (Historical Simulation), trong gi nh rng thu

nhp kinh doanh ngoi hi trn v th ngoi hi s lp li cch thc phn phi ca n

trong qu kh

Hai l, m hnh phng sai- hip phng sai, trong gi nh thu nhp kinh doanh

ngoi hi trn tng v th ngoi hi lun c phn phi chun v nhng thay i trong gi

tr ca v th ngoi hi ph thuc tuyn tnh vo thu nhp ca tt c cc cp tin t ring

l.

Ba l, Monte Carlo vi gi thit thu nhp trong tng lai s c phn phi ngu nhin.

Bng 3.1 : Tng hp cc phng php tnh VaR ph bin

Phng

php Cch thc hin u im Khuyt im

Historical

Simulation

1.Tnh gi tr hin ti ca danh

mc u t

2. Tng hp tt c cc t sut sinh

li qu kh ca danh mc u t

ny theo tng h s ri ro

3. Xp cc t sut sinh li theo th

t t thp nht n cao nht

4. Tnh VaR theo tin cy v s

liu t sut sinh li qu kh.

- Thit k v p

dng d dng

- Khng cn gi

thuyt v quy lut

phn b

- i hi mt s

liu cc ln

- Tng lai c th

khng ging qu

kh

15

Phng sai

Hip

phng sai

1.Tnh gi tr hin ti V0 ca danh

mc u t

2.T nhng d liu qu kh, tnh

t sut sinh li k vng m v

lch chun sut sinh li ca danh

mc u t

3.VaR c xc nh theo biu

thc sau y :

VaR = V0(m + zq)

- Thit k v p

dng d dng

- p dng cho

danh mc u t

bao gm chng

khon tuyn tnh

(nh c phiu)

- Tnh VaR khng

tt

cho nhng chng

khon phi tuyn

(quyn chn)

- t quan tm n

trng hp xu

nht; khng chng

minh c thuyt

v phn b chun

ca cc d liu

Monte

Carlo

1. M phng mt s lng rt ln

N bc lp

2. Cho mi bc lp i, i

16

th t gi tr t thp nht n cao

nht.

4. Tnh VaR theo tin cy v t

l phn trm s liu ri..

5. ng thi tnh sai s tng ng

cho mi VaR, nu s lng N cng

cao th sai s cng nh.

Ngun : Tng hp t tc gi

3.3 D bo phng sai :

3.3.1 M hnh tham s :

Nhng m hnh nh RiskMetrics EWMA c pht hnh nm 1996 bi hng J.P.

Morgan hay ARCH-GARCH model xut trong nghin cu ca Engle (1982) and

Bollerslev (1986) i hi cn phi xc nh c cc tham s m t hnh vi bin ng

ca t gi . V vy chng c xp vo loi m hnh tham s

Vi cch tip cn RiskMetrics, bin ng pht sinh t m hnh m hnh trung bnh trt

c trng s ly tha, gip ta tnh n nhng nh hng ca thng tin trong qu kh n

thu nhp v phng sai.

2t+1 = 2

t + (1- ) R2

t

Trong t2 l phng sai ti thi im t, rt : thu nhp ti thi im t, : nhn t phn

r, thng c mc nh l 0.94 hay 0.97. Cch tip cn ny s dng gi nh phn d

c phn phi chun

M hnh RiskMetrics c mt s u im ni bt. u tin, n cho php tnh n s thay

i ca phng sai theo cch ph hp vi bin thu nhp quan st c. Nhng mc thu

nhp cng gn th cng nh hng nhiu n phng sai ang xem xt v < 1 v v th

tc ng ca cc tr ca bnh phng thu nhp s nh dn khi tr tng dn. Th hai,

17

m hnh ny ch cha 1 bin tham s cn xc nh l . Khi c lng cho mt s

lng ln cc ti sn ti chnh RiskMetrics tm thy rng php c lng ny kh ging

nhng ti sn d liu cho. Do , n gin ha h mc nh h s = 0.94 cho mi

ti sn khi c lng phng sai hng ngy. Trong trng hp ny,khng nht thit

phi tin hnh php c lng . y l li th cho nhng danh mc u t qui m ln.

Th ba, vi nhng mu d liu t tng i cn thu thp tnh ton phng sai ngy k

tip. Trng s ca bnh phng thu nhp ngy hm nay l 1- = 0.06 v trng s l

phn r ly tha n (1- ) 99 = 0.000131 trn 100 tr ca bnh phng thu nhp. Sau

khi tnh n 100 tr ca bnh phng thu nhp, trng s tch ly l (1-) i-1

=

0.998. V vy 99,8 % ca trng s c tnh n. V vy, lng d liu cn thu thp

ch l 100 tr ca thu nhp tnh phng sai ca ngy tip theo 2t+1

M hnh GARCH

S dng m hnh t hi qui phng sai thay i c iu kin tng qut (GARCH),

phng sai d bo c th c din t nh sau :

2t+1 = + R2

t + 2

t vi +

18

thc t l phng sai trung bnh di hn c khuynh hng n nh tng i qua thi

gian. Trong khi m hnh GARCH, ngc li li c th xc nh da hon ton vo 2

2t+1 = (1- ) 2 + R2t +

2t =

2 + (R2t -

2) + (2t - 2)

T y, phng sai d bo ca ngy k tip l trung bnh c trng s ca phng sai di

hn, bnh phng thu nhp ca ngy hm nay v phng sai hm nay. Ngha l phng

sai ca ngy k tip l phng sai trung bnh di hn cng (hoc tr) nhn t hiu chnh

khi bnh phng thu nhp hm nay ln (hoc nh) hn trung bnh di hn ca n v

cng (tr) nhn t hiu chnh khi phng sai ca ngy hm nay ln (hoc nh) hn

trung bnh di hn ca n.

3.3.2 M hnh phi tham s

Nhng m hnh ny khng i hi ta phi c lng cc tham s trong phng trnh m

t hnh vi bin ng ca t gi. Cch tip cn phi tham s ph bin nht l m hnh m

phng qu kh Historical Simulation (HS). M hnh ny khng p t bt c gi nh

no cho hm phn phi thu nhp, v y l mt trong nhng u im ln nht ca n

ngoi vic n l phng php tnh ton n gin nht. V c bn, trong m hnh ny cc

mc thu nhp s c sp xp theo th t tng dn v VaR s c xc nh nh sau:

Vi danh mc gm N cp tin t. Gi tr ton danh mc ti thi im t

Thu nhp di dng log ca danh mc ti thi im t :

19

Gi chui d liu qu kh {RPF,t+1-t}m

t=1 l chui thu nhp dng log ca danh mc m

ngy trc th phn phi ca RPF,t+1 s c xc nh da vo biu tn s ca

chui {RPF,t+1-t}m

t=1

Gi tr VaR vi xc sut p s c xc nh t chui d liu qu kh nh sau:

Xc nh VaR theo phng php m phng qu kh gip ta khng phi quan tm n

cc gi nh phn phi cng nh khng phi thc hin cc php c lng. Do , loi

b tnh thiu chnh xc trong tnh ton. Mc d phng php ny c tnh n hin tng

fat tail tuy nhin n li ph thuc ch yu vo d liu qu kh v b qua cc s kin

ngoi mu, tc l n cho rng tng lai s li chnh xc nhng g qu kh din ra.

y cng l mt trong nhng yu im ln nht ca m hnh ny

3.4 Backtesting VaRs

Backtesting l mt php c lng da vo d liu thu nhp thc t nh gi mc

ph hp ca mt m hnh VaR. C th l, vi php th ny chng ta s tin hnh o

lng mc phn trm tht bi trong c lng VaR thng qua hm tn tht :

1, nu RPF,t+1 > -VaRp

t+1

0, nu RPF,t+1 < -VaRp

t+1

Lt+1 s bng 1 nu nh mc thua l thc t ngy ny ln hn mc thua l c lng

c t m hnh VaR. Trong trng hp cn li Lt+1 s bng 0.

Nhng trng hp trong mc thua l vt qu gi tr d bo l hon ton khng th

lng trc c v vy chng s c phn phi c lp trong chui thi gian nh mt

bin Bernoulli, nhn gi tr 1 vi xc sut p v gi tr 0 vi xc sut 1-p. Ta c :

H0: Lt+1 ~ i.i.d. Bernoulli (p)

Lt+1 =

20

Hm phn phi Bernoulli:

f (Lt+1,p) = (1-p)1-I,t+1

pI,t+1

p c th nhn gi tr l 1% hoc 5% ty vo mc ngha la chn trong m hnh VaR

3.4.1 Kim nh Unconditional Coverage

kim tra s cn i gia tn s thc t ca nhng dao ng bt thng vi tn s

c d bo bi cc m hnh VaR. Bi nghin cu s dng kim nh Unconditional

Coverage test.

Gi l xc sut vt ngng thc t, ta c hm hp l ca chui bin Lt+1 ~ i.i.d.

Bernoulli ()

Trong T0 v T1 l s ln Lt+1 nhn gi tr 0 v 1 trong mu quan st, vi

l gi tr c lng ca

S dng c lng hp l ti a maximum likelihood (ML) cho hm hp l ny ta c

mc ti u:

Vi gi thit H0 : = p vi p l mc ngha c la chn trong m hnh VaR. Ta c :

kim nh gi thit ny bng cch kim nh t l hp l :

21

Mt cch tim cn, khi tng s quan st, T tin ti v cc LRuc s c phn phi 2

vi

bc t do bng 1

Gi tr LRuc cng ln th xc sut gi thit H0 b bc b cng cao. V d nh vi mc

ngha l 10%, gi tr ti hn t phn phi 21 l 2.7055. Nu gi tr kim nh LRuc ln

hn 2.7055 th ta bc b m hnh VaR ny ti mc ngha 10%

3.4.2 Kim nh tnh c lp

Vn v tnh c lp xy ra khi cc s ph v m hnh VaR trong mu din ra trong

cng mt khong thi gian. iu ny c ngha l v bn cht cc nh qun tr ri ro c

th d bo c rng nu hm nay c mt s ph v th xc sut xy ra s ph v vo

ngy mai s ln hn p.100%. Trong nhng tnh hung ny h nn gia tng gi tr VaR

h thp xc sut c iu kin ca s v xung gi tr p. Mc tiu ca kim nh

ny l nhm hnh thnh mt php th gip loi b cc m hnh VaR c hin tng ph

v theo nhm

Gi nh rng cc chui dao ng bt thng l ph thuc nhau theo thi gian v c

m t bng ma trn xc sut sau :

Ma trn ny c ngha l vi iu kin Lt =0, xc sut sau Lt+1 = 1 l 01

Xc sut xy ra dao ng bt thng ngy hm sau di iu kin ngy hm nay

c mt dao ng bt thng l

22

Tng t, xc sut xy ra mt dao ng bt thng ngy hm sau di iu kin

hm nay khng xy ra dao ng bt thng

Vi T quan st , hm hp l s c xy dng nh sau :

Vi cc c lng:

T :

Ma trn s c vit li l ;

Vi vic gi nh cc chui ph v ny l ph thuc ta c 01 s khc vi 11

23

Chng ta c bit ch ti trng hp ph thuc dng. Ngha l xc sut

mt s ph v ko theo mt s ph v (11) s ln hn xc sut s khng ph v

ko theo s ph v 01

Nu, xt trn kha cnh khc, cc chui ph v ny l c lp theo thi gian, ngha l

xc sut xy ra s ph v ca ngy mai khng ph thuc vo vic ngy hm nay c xy

ra ph v hay khng th ta c 01 = 11 =

Ta c th kim nh tnh c lp vi gi thit H0 : 01 = 11 v thit lp gi tr kim nh :

Trong mt mu quan st ln th LRind cng s c phn phi 2 vi bc t do l 1. Cc

bc kim nh tng t vi kim nh mc ngha

3.4.3 Kim nh Conditional Coverage

V c bn, vn cn quan tm trong nh gi mc ph hp ca m hnh VaR l

tnh c lp ca cc ln ph v v chnh xc ca s ln ph v trung bnh

kim nh ng thi 2 tnh cht ny ta s dng php kim nh mc ngha c iu

kin, vi gi tr kim nh c thit lp nh sau :

Vi gi thit H0 : 01 = 11 = p. ta c :

24

V bn cht kim nh Kim nh Conditional Coverage l s tng hp ca 2 kim nh

Unconditional Coverage test v kim nh tnh c lp

4. P DNG M HNH VALUE AT RISK LNG HA RI RO T GI

TRONG KINH DOANH NGOI HI

4.1 Khung l thuyt c s v vn ri ro trong kinh doanh ngoi hi

4.1.1 c im ca kinh doanh ngoi hi trn th trng forex:

Th nht l ph giao dch thp v khng phi qua trung gian t lnh : nh u t giao

dch trc tip vi th trng trn cc phn mm giao dch vi sn v c cp nht

thng tin trc tip v gi v t gi cc cp tin t. iu ny lm gim chi ph giao dch,

thc y tin giao dch din ra nhanh chng v hn ch kh nng xy ra nhng hiu

lm trong qu trnh thc hin cc lnh giao dch.

Th hai l th trng giao dch 24h : nh vy m nh u t khng phi ch i th

trng ng v m ca, c th linh hot trong vic chn thi gian giao dch. ng thi,

c im ny cng cho php nhng ch th tham gia th trng vo v thot ra bt c

lc no.

Th ba l th trng c t sut n by (leverage trading) hp dn : thng mc cao

1:100 , 1:200 iu ny dn ti gia tng khong sinh li tim nng ca nh u t

Th t l th trng hot ng c lp, khng ai c kh nng nh hng th trng : l

th trng ton cu vi khi lng giap dch khng l cng vi s a dng thnh phn

25

v ng o lc lng tham gia th trng dn ti khng ai c th iu khin v kim

sot c th trng trong di hn. C th l, s can thip ca ngn hng trung ng ch

c tc dng trong ngn hn v khng hiu qu. Ngn hng, qu u t, chnh ph, nh

u c, v cc nhm giao dch ch l mt thnh phn nh ca th trng ngoi hi.

Nhng phn tch ca cc chuyn gia ch mang tnh cht tham kho ch khng th tc

ng mnh ln th trng ny.

Th nm l th trng hot ng mang tnh xu hng (Trendiness) : trong mt nhng

khong thi gian lch s, tin t khng nh c tnh xu hng quan trng ca n.

Mi ng tin mang mt tnh cch ring v a ra ch mt xu hng, bt k nhng

nh hng v nhng c hi giao dch a dng trn th trng.

4.1.2 Cc loi ri ro nguyn nhn pht sinh ri ro trong giao dch kinh

doanh ngoi hi:

Phn loi theo hng tng qut

C 2 dng ri ro cn bn:

Ri ro h thng (systematic risks) : l loi ri ro c th nh hng n s bin ng ca

nhiu cp tin t. V d nh : nhng s kin chnh tr mang tnh ton cu, thm ha thin

nhin hay vn chin tranh

Ri ro khng h thng (specific risks): ri ro mang tnh c th ring bit, ch nh hng

n vi loi tin, vi cp tin. V d nh cc tin tc kinh t c nh hng n 1 nc

hoc 1 vng no nh mt cuc nh cng hoc 1 s iu chnh trong li sut ca

ng CAD

hn ch ri ro khng h thng nh u t c th la chn phng thc a dng ha

u t trong danh mc u t bao gm nhiu cp tin khc nhau

26

Phn loi chi tit

Ri ro t gi (exchange rate risks): l ri ro thng trc, gn lin v tr thnh ri ro c

trng ca hot ng kinh doanh ngoi hi

Nguyn nhn pht sinh :

Th nht l do v th ngoi hi khng tng xng: nh kinh doanh ngoi hi ch

chu ri ro t gi khi duy tr mt trng thi ngoi hi m. V vy vn t ra trong

qun tr ri ro ngoi hi l lm th no qun l tt trng thi mua bn ngoi t ngn

nga ri ro t gi pht sinh

Th hai l do nh hng bi cc nhn t khc nh cung cu ngoi t trn th trng,

cn cn thanh ton quc t, chnh sch thu quan, nng sut lao ng, tnh hnh chnh tr

ca mi nc, li sut ng ngoi t v ni t.

Ri ro li sut (interest rate risks) : s tng gim li sut ng tin trong cp tin vo

thi gian giao dch s nh hng n lng tin li/ph c th phi tr cho nh mi gii

hng ngy duy tr lnh giao dch

Ri ro thanh khon (liquidity risks): ri ro ny pht sinh khi cng ty mi gi ti khon

giao dch khng cn kh nng thanh ton khi ch ti khon yu cu rt tin. V vy,

nh u t cn cn trng trong la chn cng ty mua gii khi tham gia giao dch kinh

doanh ngoi hi

Ri ro k thut (Technology risks): s gin on, hng hc ca cc thit b giao dch, hay

li ng truyn mng . Do tnh cht ton cu ha a phn giao dch ngoi hi u ph

thuc vo cng ngh, song y l dng ri ro m nhiu nh u t t quan tm n. V

vy hn ch nh hng xu t ri ro ny, cn phi c nhng d phng v ng

mng thay th khi cn thit, ng thi d phng my khi my tnh chnh b hng hc.

27

4.1.3 Vn trng thi ngoi hi (exchange position)

Trng thi ca mt ngoi t l s chnh lch gia tng s mua vo v bn ra ca ngoi t

ti mt thi im nht nh

Trng thi ng (close position) : - = 0

Trng thi m (open position): - 0

Trong :

Trng thi trng (long position) - 0

Trng thi on (short position) - 0

Bng 4.1: Tng hp cc giao dch lm pht sinh trng thi ngoi hi

Trng thi trng (long position) Trng thi on (short position)

Mua ngoi t (spot, forward) Bn ngoi t (spot, forward)

Thu li cho vay bng ngoi t Tr li vay bng ngoi t

Thu ph dch v bng ngoi t Chi tr ph dch v bng ngoi t

Nhn chuyn tin ngoi t Chuyn ngoi t i.

Ngun : Tng hp t tc gi

Xc nh trng thi ngoi t

EPX,t : trng thi ngoi t X ti thi im t

LPx, t0 t : doanh s pht sinh trng thi trng ca ngoi t X trong thi k t0 t

SPX, t0 t : doanh s pht sinh trng thi on ca ngoi t X trong thi k t0 t

Trng thi ngoi t s c xc nh da vo cng thc sau:

28

Cch 1 : EPX(t) = LPX (t0 t) SPX (t0 t)

Cch 2 : EPX(t) = EPX(t-1) +LPX (t) SPX (t)

Ngoi ra i vi mi thi k cng s c nhng qui nh v tng trng thi ngoi t ca

tt c ngoi t c qui i theo ng ni t

4.1.4 Vn qun tr ri ro trong kinh doanh ngoi hi

ngn nga v ch ng i ph vi nhng ri ro pht sinh trong kinh doanh ngoi

hi. Mt s vn chnh sau y cn c c bit ch :

Th nht l cn c s duy tr tnh cn xng v trng thi ngoi hi: qun l bng cng c

hn mc (position limit). Trong :

Nguyn tc phn b hn mc: thng da vo kinh nghim thm nin v kh

nng kinh doanh trn th trng forex ca nh u t

Hn mc theo cc ng tin kinh doanh: c ngha l i vi nhng ng tin

bin ng thp th hn mc phn b cao hn v ngc li nhng ng tin bin

ng cao s c mc hn mc thp hn

Ngoi ra cn c th thc hin thit lp hn mc cho tng loi nghip v c th.

ng thi kt hp vi vic s dng linh hot cc cng c lnh giao dch

Th hai, cn c mt s a dng ha danh mc u t hp l : trong thc hin giao

dch vi nhiu loi ngoi t khc nhau v s dng kt hp nhiu loi nghip v kinh

doanh trn th trng ngoi hi

Th ba l cn chn mc n by thch hp v mc margin requirement hp l

Th t l vic t chc hot ng kinh doanh cn c nh hng, k hoch. Trong , k

hoch cn phi m bo nhng tiu chun nht nh: (1) loi c cu thi gian s dng

29

giao dch, (2) tm kim nhng tn hiu ch dn nhn bit xu hng, (3) tm kim tn

hiu ch dn gip xc nhn xu hng chung, (4) xc nh mc chp nhn ri ro, (5)

xc nh thi gian nhp cuc v thot khi phin giao dch, (6) t nhng qui nh cho

h thng giao dch v kim tra h thng giao dch

V cui cng cn lu rng khng c mt loi ri ro no l thch hp vi tt c cc nh

u t, mi nh u t s c kh nng sn sng chp nhn mc ri ro khc nhau. S

chp nhn ri ro ny khng phi l mt mc c nh m thay i ty thuc vo k nng

v s hiu bit ca nh u t khi tham gia th trng. Vn l cn c lng c

mc t l gia ri ro sn sng chu ng v mc ri ro c th chp nhn c nu xy ra

trong thc t . T thit lp c mt k hoch kinh doanh hp l nhm t c s

cn bng gia ri ro v li nhun tim nng.

4.2 D liu v xy dng m hnh thc nghim

Bi nghin cu s dng d liu thu nhp kinh doanh ngoi hi theo tn s hng ngy

ca 7 cp t gi c doanh s giao dch ln trn th trng forex GBP/USD, EUR/USD,

AUD/USD, CHF/ USD, NZD/USD, JPY/USD cho mu thi gian 6 nm 1/1/2006-

1/11/2012 (bao gm 2192 quan st). Thu nhp c tnh trn c s phng php logarit

Rt = ln(St/St-1) trong St v St-1 ln lt l t gi ngy th t v t-1.

Bng 4.2 : Thng k m t thu nhp ca cc cp tin t trong giai on 1/11/2006-

1/11/2012

GBP EUR CAD AUD CHF NZD JPY

Mean -7.65E-05 8.85E-06 5.43E-05 0.000135 0.000134 9.51E-05 0.000176

Median 0.000000 0.000000 0.000000 0.000100 0.000000 0.000100 0.000000

Maximum 0.031400 0.034600 0.041700 0.052900 0.038300 0.047300 0.029000

Minimum -0.039900 -0.025200 -0.038100 -0.061400 -0.045300 -0.047900 -0.032000

Std. Dev. 0.004619 0.004746 0.004945 0.007060 0.005069 0.007031 0.006005

Skewness -0.748269 0.034628 -0.222315 -0.477176 -0.220738 -0.467170 -0.147762

Kurtosis 12.36901 7.371491 9.817916 13.20338 13.67035 8.635094 6.116667

Jarque-Bera 8221.635 1745.812 4263.593 9591.800 10416.69 2979.958 895.1533

Probability 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000

30

Ngun : Theo tnh ton t tc gi

Kim nh tnh dng

Bi nghin cu s tin hnh kim nh tnh dng ca cc bin qua kim nh nghim

n v theo phng php Augmented Dickey-Fuller (ADF) test.

Bng 3.2 (xem phn Ph lc) trnh by kt qu kim nh nghim n v Augmented

Dickey-Fuller (ADF) test v tnh dng ca chui cc bin. Kt qu cho thy, v c bn

cc chui d liu ang xem xt u dng 2 mc ngha 1% v 5% trong trng hp

hi quy c chn, khng xu th v hi quy c chn c xu th.

5. KT QU THC NGHIM :

5.1 Kt qu xc nh VaR cho tng cp tin t ring l:

Bi nghin cu s dng 3 phng php tip cn : M hnh HS, m hnh RiskMetrics cho

d liu hng ngy vi nhn t phn r bng 0.94 v m hnh GARCH (1,1) tnh ton

gi tr VaR vi 2 tin cy l 99% v 95 %. T tin hnh d bo VaR cho ngy tip

theo ca chui (quan st th 2193). Kt qu d bo c trnh by trong bng 5.1 v

bng 5.2 vi cc n v tnh l phn trm v gi tr tuyt i theo n v dollar.

Bng 5.1: Kt qu tnh VaR cho tng cp tin t (n v %)


VaR

99%

RM Daily 0.55% 0.69% 0.60% 0.70% 0.64% 0.81% 1.11%

10 days 1.75% 2.18% 1.89% 2.20% 2.03% 2.57% 3.52%

GARCH(1,1) Daily 0.61% 0.79% 0.68% 0.84% 0.72% 1.00% 1.21%

10 days 1.91% 2.49% 2.16% 2.66% 2.28% 3.15% 3.81%

HS Daily 0.68% 0.89% 0.63% 0.93% 0.93% 1.11% 0.82%

10 days 2.15% 2.82% 1.98% 2.94% 2.93% 3.51% 2.60%

VaR

95%

RM Daily 0.39% 0.49% 0.42% 0.49% 0.45% 0.57% 0.79%

10 days 1.24% 1.54% 1.34% 1.56% 1.44% 1.81% 2.49%

GARCH(1,1) Daily 0.43% 0.56% 0.48% 0.59% 0.51% 0.71% 0.85%

Sum -0.167600 0.019400 0.119100 0.295300 0.293000 0.208400 0.386100

SumSq. Dev. 0.046742 0.049350 0.053576 0.109212 0.056291 0.108326 0.078995

Observations 2192 2192 2192 2192 2192 2192 2192

31

10 days 1.35% 1.76% 1.53% 1.88% 1.61% 2.23% 2.69%

HS Daily 0.46% 0.56% 0.46% 0.71% 0.57% 0.71% 0.81%

10 days 1.47% 1.77% 1.44% 2.25% 1.80% 2.23% 2.55%

Ngun: Theo tnh ton t tc gi

Bng 5.2 : Kt qu tnh VaR cho tng cp tin t ring l (n v USD)


VaR

99%

RM

Daily $11,053 $13,727 $11,938 $13,886 $12,801 $16,158 $22,150

10

days $34,745 $43,089 $37,510 $43,580 $40,200 $50,650 $69,208

GARCH(1,1)

Daily $12,073 $15,670 $13,641 $16,742 $14,340 $19,853 $23,955

10

days $37,934 $49,134 $42,821 $52,462 $44,996 $62,107 $74,774

HS

Daily $13,576 $17,755 $12,485 $18,498 $18,425 $22,057 $16,392

10

days $42,617 $55,610 $39,216 $57,913 $57,686 $68,903 $51,382

VaR

95%

RM

Daily $7,823 $9,716 $8,448 $9,828 $9,059 $11,437 $15,686

10

days $24,629 $30,562 $26,596 $30,913 $28,509 $35,947 $49,185

GARCH(1,1)

Daily $8,546 $11,093 $9,655 $11,851 $10,150 $14,056 $16,968

10

days $26,896 $34,867 $30,373 $37,239 $31,921 $44,116 $53,165

HS Daily $9,259 $11,189 $9,119 $14,209 $11,368 $14,050 $16,075

10

days $29,110 $35,181 $28,674 $44,582 $35,727 $44,079 $50,381


Hnh 5.1: Kt qu d bo VaR cho tng cp tin t ring l

32


5.2 Xc nh hn mc u t, li nhun v thua l tch ly ca danh mc da

vo gi tr VaR

T gi tr VaR, bi nghin cu s tip tc tin hnh xc nh hn mc u t ti a hng

ngy. Gi nh mi ngy nh u t c mc gii hn VaR 99% l $2000,000. m

bo mc an ton, lng u t mi ngy phi tha iu kin

$Positiont+1

V vy mc u t ti a cho mi ngy s l

33

$Positiont+1

T ta c mc li nhun/thua l (P/L) hng ngy: (P/L)t+1 = $Positiont+1 (St+1/St -1)

Kt qu P/L tch ly hng ngy ca tng cp tin t trong danh mc s c trnh by

trong hnh 5.2

Hnh 5.2: Ktqu P/L tch ly hng ngy ca tng cp tin t


34

5.3 Kim tra m hnh Backtesting VaRs

kim tra tnh thch hp ca cc m hnh VaR xy dng, php th Backtesting s

c thc hin da trn 3 kim nh chnh nh trnh by trn l kim nh

Unconditional coverage, kim nh tnh c lp v im nh tng hp Conditional

coverage. Cc kim nh ny thc hin theo phn phi 2 vi mc ngha 10% v bc

t do 1 (cho 2 kim nh u) v 1 (cho kim nh cui cng)

Bng 5.3: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t GBP/USD

Test Statistics

RiskMetrics Historical Simulation GARCH(1,1)

1% 5% 1% 5% 1% 5%

T0 1655 1586 1664 1608 1655 1597

T1 36 105 27 83 36 94

T00 1622 1501 1645 1545 1622 1525

T01 33 85 19 62 33 72

T10 33 85 19 63 33 72

T11 3 20 8 21 3 22

2.13% 6.21% 1.60% 4.91% 2.13% 5.56%

2.22E-76 1.30E-171 7.16E-61 1.59E-144 2.22E-76 2.30E-158

L(p) 5.97E-80 1.15E-172 5.46E-62 1.56E-144 5.97E-80 1.34E-158

1.99% 5.36% 1.14% 3.86% 1.99% 4.51%

8.33% 19.05% 29.63% 25.30% 8.33% 23.40%

L 1.65E-75 7.30E-167 5.81E-53 2.75E-135 1.65E-75 2.11E-150

LRuc 16.443 4.851 5.149 0.030 16.443 1.075

LRind 4.013 21.868 36.423 42.549 4.013 36.669

LRcc 19.224 37.369 47.844 60.796 20.456 37.744


LRuc Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

LRind Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

LRcc Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model


35

Bng 5.4:Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t EUR/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1656 1578 1657 1590 1657 1588

T1 35 113 34 101 34 103

T00 1624 1489 1632 1518 1627 1507

T01 32 89 25 72 30 81

T10 32 89 25 72 30 81

T11 3 24 9 29 4 22

2.07% 6.68% 2.01% 5.97% 2.01% 6.09%

1.04E-74 6.60E-181 4.98E-73 7.36E-167 4.98E-73 3.03E-169

L(p) 5.91E-78 6.78E-183 5.85E-76 1.50E-167 5.85E-76 4.16E-170

1.93% 5.64% 1.51% 4.53% 1.81% 5.10%

8.57% 21.24% 26.47% 28.71% 11.76% 21.36%

8.84E-74 8.83E-175 1.43E-65 2.39E-154 2.99E-71 7.11E-163

LRuc 14.937 9.157 13.490 3.180 13.490 3.974

LRind 4.287 28.212 34.354 57.615 8.191 29.334

LRcc 19.224 37.369 47.844 60.796 21.681 33.308

Hypothesis Testing (Chi-Square Test)

Significance level =10%


LRuc Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

LRind Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

LRcc Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model


Bng 5.5:Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t CAD/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1667 1584 1674 1612 1669 1595

T1 24 107 17 79 22 96

T00 1644 1492 1660 1553 1648 1512

T01 23 92 14 59 21 83

T10 23 92 14 59 21 83

36

T11 1 15 3 20 1 13

1.42% 6.33% 1.01% 4.67% 1.30% 5.68%

2.00E-55 5.83E-174 4.94E-42 2.48E-139 1.05E-51 8.14E-161

L(p) 5.30E-56 3.19E-175 4.94E-42 2.04E-139 5.19E-52 3.72E-161

1.38% 5.81% 0.84% 3.66% 1.26% 5.20%

4.17% 14.02% 17.65% 25.32% 4.55% 13.54%

3.09E-55 4.84E-172 2.62E-39 4.85E-130 1.84E-51 6.75E-159

LRuc 2.657 5.809 0.000 0.392 1.414 1.567

LRind 0.873 8.841 12.548 42.788 1.122 8.836

LRcc 3.530 14.650 12.548 43.180 2.536 10.403


Bng 5.6:Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t AUD/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1655 1585 1671 1605 1660 1593

T1 36 106 20 86 31 98

T00 1620 1495 1655 1540 1629 1508

T01 35 90 16 65 31 85

T10 35 90 16 65 31 85

T11 1 16 4 21 1 13

2.13% 6.27% 1.18% 5.09% 1.83% 5.80%

2.22E-76 8.67E-173 6.66E-48 2.31E-148 6.62E-68 3.01E-163

L(p) 5.97E-80 6.06E-174 5.09E-48 2.28E-148 5.68E-70 1.03E-163

2.11% 5.68% 0.96% 4.05% 1.87% 5.34%

2.78% 15.09% 20.00% 24.42% 3.13% 13.27%

2.30E-76 2.45E-170 2.73E-44 1.18E-139 1.38E-69 1.75E-161

LRuc 16.443 5.320 0.539 0.026 9.516 2.147

LRind 0.068 11.289 16.639 40.109 -7.742 8.118

LRcc 16.511 16.609 17.178 40.135 1.774 10.265




LRuc Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

LRind Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

LRcc Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

37


Bng 5.7: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t CHF/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1657 1604 1660 1589 1660 1613

T1 34 87 31 102 31 78

T00 1625 1531 1634 1508 1632 1545

T01 32 73 26 81 28 68

T10 32 73 26 81 28 68

T11 2 14 5 21 3 10

2.01% 5.14% 1.83% 6.03% 1.83% 4.61%

4.98E-73 1.24E-149 6.62E-68 4.70E-168 6.62E-68 5.09E-138

L(p) 5.85E-76 1.20E-149 5.68E-70 7.90E-169 5.68E-70 3.87E-138

1.93% 4.55% 1.57% 5.10% 1.69% 4.22%

5.88% 16.09% 16.13% 20.59% 9.68% 12.82%

1.20E-72 2.52E-146 8.24E-65 3.22E-162 1.05E-66 4.15E-136

LRuc 13.490 0.074 9.516 3.567 9.516 0.548

LRind 1.768 15.229 14.252 26.871 5.522 8.802

LRcc 15.258 15.303 23.768 30.438 15.038 9.350





LRuc Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

LRind Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

LRcc Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model


LRuc Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

LRind Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

LRcc Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

38

Bng 5.8:Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t NZD/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1650 1595 1672 1614 1656 1601

T1 41 96 19 77 35 90

T00 1610 1512 1653 1551 1622 1523

T01 40 83 19 63 34 78

T10 40 83 19 63 34 78

T11 1 13 1 14 1 12

2.42% 5.68% 1.12% 4.55% 2.07% 5.32%

1.52E-84 8.14E-161 5.71E-46 1.06E-136 1.04E-74 2.10E-153

L(p) 6.28E-90 3.72E-161 5.04E-46 7.36E-137 5.91E-78 1.75E-153

2.42% 5.20% 1.14% 3.90% 2.05% 4.87%

2.44% 13.54% 5.26% 18.18% 2.86% 13.33%

1.52E-84 6.75E-159 1.33E-47 3.85E-132 1.09E-74 1.81E-151

LRuc 24.793 1.567 0.251 0.731 14.937 0.362

LRind 0.000 8.836 -7.512 21.001 0.098 8.911

LRcc 24.793 10.403 -7.261 21.731 15.035 9.274


Bng 5.9: Kt qu kim tra Backtesting cho m hnh VaR ca cp tin t JPY/USD

Test Statistics


1% 5% 1% 5% 1% 5%

T0 1665 1565 1676 1661 1672 1605

T1 26 126 15 30 19 86

T00 1640 1453 1661 1633 1654 1528

T01 25 113 15 28 18 77

T10 25 112 15 28 18 77

T11 1 13 1 2 1 9

1.54% 7.45% 0.89% 1.77% 1.12% 5.09%


LRuc Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

LRind Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

LRcc Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Reject

VaR model

Reject

VaR model

39

4.50E-59 1.87E-195 5.42E-38 3.60E-66 5.71E-46 2.31E-148

L(p) 5.40E-60 1.61E-199 4.84E-38 9.29E-77 5.04E-46 2.28E-148

1.50% 7.22% 0.89% 1.69% 1.08% 4.80%

3.85% 10.32% 6.67% 6.67% 5.26% 10.47%

6.26E-59 4.03E-195 1.47E-39 1.26E-65 1.26E-45 1.97E-147

LRuc 4.239 18.711 0.227 48.763 0.251 0.026

LRind 0.662 1.542 -7.217 2.510 1.583 4.285

LRcc 4.901 20.253 -6.991 51.273 1.833 4.311


T cc kt qu chp nhn hoc bc b m hnh VaR tng hp trn ta c th a ra kt

lun v mc hot ng ca cc m hnh HS, RiskMetrics, GARCH (1,1) ti 2 mc

ngha : mc an ton 1% v mc cnh bo hn 5%. Trn c s la chn c m hnh

VaR thch hp cho vic ra quyt nh u t i vi tng cp tin t nm trong danh

mc.

Phn tip theo ca bi nghin cu s tin hnh xc nh gi tr VaR cho ton b danh

mc. Trong c tnh n t trng ca tng cp tin, tng tc gia cc bin ng v

phn tch cho thy li ch thu c t vic a dng ha u t.

5.4 Xc nh VaR cho c danh mc

i vi danh mc u t bi nghin cu la chn r tin t gm 7 cp tin c doanh s

giao dch ln nht trn th trng ngoi hi. Trong mc ri ro ca danh mc s

c tnh ton da trn ma trn VAR-COVAR




LRuc Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

LRind Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

Reject VaR

model

LRcc Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Reject

VaR model

Don't Reject

VaR model

Don't Reject

VaR model

40

Bng 5.10 Ma trn phng sai ca cc bin


Bng 5.11 Ma trn tng quan gia cc bin


GBP 1.000000 0.652350 0.543942 0.608540 0.439179 0.598801 -0.086342

EUR 0.652350 1.000000 0.548975 0.636670 0.724104 0.625330 0.082953

CAD 0.543942 0.548975 1.000000 0.725011 0.317643 0.669558 -0.189959

AUD 0.608540 0.636670 0.725011 1.000000 0.364527 0.858912 -0.206986

CHF 0.439179 0.724104 0.317643 0.364527 1.000000 0.382959 0.276215

NZD 0.598801 0.625330 0.669558 0.858912 0.382959 1.000000 -0.165678

JPY -0.086342 0.082953 -0.189959 -0.206986 0.276215 -0.165678 1.000000


Bng 5.12 trnh by kt qu tnh VaR cho tng cp t gi ring l v cho ton b danh

mc u t. n gin, bi nghin cu gi nh t trng tng ng tin trong danh

mc ln lt l GBP (10%), EUR (15%), CAD (10%), AUD (25%), CHF (20%), NZD

(10%), JPY (10%). (trong thc t, xc nh t trng u t ti u, c th da vo

nguyn tc phn b Pareto). M hnh VaR c xy dng vi d liu t gi hng ngy

v tin cy 99%. o lng hiu ng tc ng qua li gia bin ng cc cp tin,

bi nghin cu s xc nh da trn ma trn phng sai- hip phng sai. Theo kt qu

m hnh cho thy, gi tr VaR o lng c cho ton danh mc khi c tnh n s

tng tc nh hn rt nhiu so vi tng gi tr VaR cho tng cp tin t ring l (0.8%

so vi 3.34%). iu ny cho thy tc ng rt ln ca vic a dng ha danh mc u

t, n gip gim thiu ti a cc ri ro phi h thng khi nh u t s hu mt danh mc

c a dng ha tt. ng thi kt qu trn cho thy : c 1% xc sut cho vic khon


GBP 2.13E-05 1.43E-05 1.24E-05 1.98E-05 1.03E-05 1.94E-05 -2.39E-06

EUR 1.43E-05 2.25E-05 1.29E-05 2.13E-05 1.74E-05 2.09E-05 2.36E-06

CAD 1.24E-05 1.29E-05 2.44E-05 2.53E-05 7.96E-06 2.33E-05 -5.64E-06

AUD 1.98E-05 2.13E-05 2.53E-05 4.98E-05 1.30E-05 4.26E-05 -8.77E-06

CHF 1.03E-05 1.74E-05 7.96E-06 1.30E-05 2.57E-05 1.36E-05 8.40E-06

NZD 1.94E-05 2.09E-05 2.33E-05 4.26E-05 1.36E-05 4.94E-05 -6.99E-06

JPY -2.39E-06 2.36E-06 -5.64E-06 -8.77E-06 8.40E-06 -6.99E-06 3.60E-05

41

l ngy mai s vt mc 0.8% gi tr danh mc ngy hm nay. Nu gi tr danh mc

ngy hm nay l 2 triu dollar th $ Var s l :

$VaR = VPF (1- exp (-VaR)) = 2000000 (1- exp (-0.008)) = $ 15936.17

Bng 5.12 Kt qu tnh VaR cho ton danh mc

GBP

Variance 0.000021

Weight 10%

VaR 0.34%

EUR

Variance 0.000023

Weight 15%

VaR 0.43%

CAD

Variance 0.000024

Weight 10%

VaR 0.36%

AUD

Variance 0.000050

Weight 25%

VaR 0.82%

CHF

Variance 0.000026

Weight 20%

VaR 0.53%

NZD

Variance 0.000049

Weight 10%

VaR 0.52%

JPY

Variance 0.000036

Weight 10%

VaR 0.44%

Portfolio

Variance 0.000012

VaR 0.80%

Sum of individual VaRs 3.44%

6. KT LUN

Thng qua vic ng dng m hnh Value at risk trong lng ha ri ro kinh doanh ngoi

hi trn th trng Forex, bi nghin cu a ra c nhng kt qu kho st thc

nghim qui trnh ng dng VaR trong thc tin u t, gii quyt cc vn lng ha

nhng bin ng ca d liu ti chnh (chui t gi) thng qua cc m hnh d bo

phng sai tham s v phi tham s. ng thi, t vic khai thc gi tr VaR, bi nghin

42

cu cng tin hnh xc nh mt s thng tin chi tit cho vic lp k hoch u t ,

c th l vic xc nh hn mc u t ti a v li nhun/thua l (P/L) tch ly d kin.

Cui cng l, vi nhng yu t hnh thnh m hnh nh : vn phn phi xc sut, la

chn khung thi gian v tin cy, bi nghin cu cng tin hnh thit lp v kim

nh thc t a ra kt lun v tnh thch hp v ti u ca m hnh. Nhn chung c

th thy, vic xc nh mt m hnh ph hp v cho kt qu d bo chnh xc ph thuc

phn ln vo c tnh ca chui d liu, v vy khng c mt m hnh no l chun i

vi nh u t, vic kho st thc t v lin tc c cc php th kim nh l v cng

cn thit a ra nhng iu chnh kp thi.

T nhng kt lun trn a ra mt vi im cn lu trong vic vn dng VaR trong

thc tin:

Th nht, m hnh ny s dng d liu qu kh d bo cc hnh vi trong tng lai.

Tuy nhin, v lch s khng phi lc no cng phn nh c tng lai, nht l i vi

nhng yu t khng chc chn lin quan n hnh vi con ngi. V s liu trong qu

kh kh c th phn nh c nhng s kin kiu nh "black swan" s xy ra trong

tng lai nn trong qu trnh c lng bng d liu qu kh, phi ht sc ch trng

n vic la chn d liu ph hp v nht l khng b st nhng s kin quan trng,

Th hai, m hnh c xy dng da trn cc gi nh khng phi lun thch hp trong

tt c cc iu kin. V vy, ngi dng cn ht sc cn trng i vi nhng gii hn

ca m hnh v xc nh hm cho cc tnh ton ca mnh.

Th ba, gi tr VaR d bo ch c th c s dng ra quyt nh ng khi ngi

dng c kin thc v khi nim gi tr ti ri ro cng nh qu trnh xy dng m hnh.

Cui cng, nh G.Box tng ni: "all models are wrong but some are useful".VaR l

mt phng php c nh gi cao v n p ng c c bn cc nhu cu cn thit

ca mt nh u t nh: nh gi ri ro, gii hn ri ro, thit lp cc ngng an ton

vn, phn b vn ni b. Tuy nhin, VaR vn cha phi l cu tr li hon ho cho cc

thch thc t ra trong qu trnh qun tr ri ro, nht l khi n cn bc l nhng yu

43

im nht nh. Gii nghin cu cng nh cc nh u t vn cn kh nhiu bn khon

v hiu qu thc s ca m hnh ny. Song, c mt thc t l VaR suy cho cng cng

ch l mt con s, mt cng c khng hm ngha tuyt i. V vy, vn hiu qu s

ph thuc vo vic n nm trong tay mt ngi s dng nh th no? S xut hin

ca VaR l tm im m ra thi k nghin cu v pht trin mi trong lnh vc lng

ha v qun tr ri ro. Do , c th ni y vn l mt cng c o lng ri ro mang

nhiu ha hn trong tng lai.

a

DANH MC TI LIU THAM KHO

Ti liu ting Anh

1. Alexander, C. (2001), Market Models: A Guide to Financial Data Analysis,

John Wiley & Sons, West Sussex.

2. Barone-Adesi and Giannopoulos (2000), VaR Modelling on Long Run

Horizons, Journal Automation and Remote Control Volume 64 Issue 7, July

2003 ,Pages 1094 - 1100

3. Brooks, C., A. D. Clare, J.W. Dalle Molle, and G. Persand (2003), A

Comparison of Extreme Value Theory Approaches for Determining Value at

Risk, Journal of Empirical Finance, Forthcoming, Cass Business School

Research Paper.

4. Caserta, S. and C. G. de Vries (2003), Extreme Value Theory and Statistics for

Heavy Tail Data, Modern Risk Management A History, Field, P. (ed.), 169-

178, RISK Books, London.

5. Christoffersen, PeterF. Elements of nancial risk management/ Peter

Christoffersen.2nd ISBN 978-0-12-374448-7

6. Cotter, J. and K. Dowd (2007), The tail risks of FX return distributions: a

comparison of the returns associated with limit orders and market orders,

MPRA Papers series at University Library of Munich, Germany.

7. Dacorogna, M. M. and P. Blum (2002), "Extreme Moves in Foreign Exchange

Rates and Risk Limit Setting," EconWPA Risk and Insurance Series, reference

0306004

8. Duffie, D. and J. Pan (1997), "An Overview of Value at Risk", Journal of

Derivatives, 7-49.

9. Embrechts, P., C. Kluppelberg, and T. Mikosch (1997), Modelling Extremal

Events for Insurance and Finance, Springer-Verlag, Berlin.

b

10. Engel, J. and M. Gizycki (1999), Conservatism, Accuracy and Efficiency:

Comparing Value-at-Risk Models, Working Paper at Reserve Bank of

Australia, Sydney.

11. Engle (1982) AutoRegressive Conditional Heteroskedasticity, Nobel lecture

12. Gonzalo J. and J. Olmo (2004), Which Extreme Values are Really Extreme?,

Journal of Financial Econometrics, 2.3, 349-369.

13. Hendricks, D. (1996), Evaluation of Value-at-Risk Models Using Historical

Data, Economic Policy Review, 2, 39-70

14. Hols, M. A. C. B and C. G. de Vries (1991), The Limiting Distribution of

Extremal Exchange Rate Returns, Journal of Applied Econometrics, 6.3., 287-

302.

15. Huisman, R., K. Koedijk, C. Kool, and F. Palm (2001), Tail Index Estimates

in Small Samples, Journal of Business and Economic Statistics, 19, 208-216.

16. Huisman, R., K. Koedijk, C. Kool, and F. Palm (1998), The Fat-Tailedness of

FX returns, Working Paper at University of Maastricht, Department of

Economics, Center for Economic Studies and Ifo Institute for Economic

Research, Maastricht.

17. Jorion, P. (2001), Value at Risk - The New Benchmark for Managing Financial

Risk, 2nd Edition, McGraw-Hill, New York.

18. Kaplanski, G. and H. Levy (2009), Value-at-Risk Capital Requirement

Regulation, Risk Taking and Asset Allocation: A Mean-Variance Analysis,

Working Paper available at http://ssrn.com/abstract=1081288.

19. Matthys G. and J. Beirlant (2000), Adaptive Threshold Selection in Tail Index

Estimation, in P. Embrechts (ed.), Extremes and Integrated Risk Management,

37-49, RISK Books, London.

20. McNeil, A.J. (1997a), Estimating the Tails of Loss Severity Distributions

Using Extreme Value Theory, ASTIN Bulletin, 27, 117-137.

c

21. McNeil, A.J. (1997b), The Peaks over Threshold Method for Estimating High

Quantiles of Loss Distributions, ETH preprint (www.math.ethz.ch/~mcneil).

22. McNeil, A.J. (1998), Calculating Quantile Risk Measures for Financial Return

Series Using Extreme Value Theory, ETH preprint

(www.math.ethz.ch/~mcneil).

23. Resnick, S. (2007), Heavy-Tail Phenomena Probabilistic and Statistical

Modelling, Springer, New York, 73-114.

24. Robert, C. Y., J. Segers, and C. A. T. Ferro (2008), A Sliding Block Estimator

for the Extremal Index, Working Paper at Statistics Institute, Catholic

University of Louvain, Belgium.

25. Rockafellar, R.T. and S. Uryasev (2002), Conditional Value-at-Risk for

General Loss Distribution, Journal of Banking and Finance, 26, 1443-1471.

26. Wagner, N. and T. Marsh (2003), Measuring Tail Thickness under GARCH

and an Application to Extreme Exchange Rate Changes, Working Paper at

Haas School of Business, University of California Berkeley, California.

Ti liu ting Vit

1. Nguyn Minh Kiu.(2008) Th trng ngoi hi v cc gii php phng nga

ri ro (Qun tr ri ro ti chnh) / NXB Thng K, 2008.

2. Trn Hong Ngn, Nguyn Minh Kiu (2007) Gio trnh Thanh ton quc t /

NXB Thng k, 2007.

d

PH LC

Hnh 4.1 : Biu phn phi tn sut ca cc cp tin t

JPY


GBP EUR CAD

AUD CHF NZD

e

Hnh 4.2 : Bin ng t gi hng ngy ca cc cp tin t

ngun : Theo tnh ton t tc gi

f

Bng 4.3 : Kim nh ADF test v tnh dng ca cc bin

ADF Unit Root Test

I TI GBP -30.9571(*)(**) S -30.9551(*)(**) S EUR -30.5633(*)(**) S -30.5713(*)(**) S CAD -30.4164(*)(**) S -30.4101(*)(**) S AUD -36.6483(*)(**) S -36.6399(*)(**) S CHF -30.2275(*)(**) S -30.2243(*)(**) S NZD -36.0676(*)(**) S -36.0602(*)(**) S JPY -47.8223(*)(**) S -47.8145(*)(**) S

Lu : I, TI : hi quy c chn, khng xu th v c chn, c xu th. *,** th hin c kh nng bc b gi thit Ho: chui c nghim n v mc ngha ln lt l1% v 5%. S/N dng v khng dng.

Bng 4.4: Kt qu o lng bin ng ca cc cp t gi bng m hnh

GARCH (1,1)

Dependent Variable: GBP

Method: ML ARCH

Date: 11/17/12 Time: 20:37

Sample (adjusted): 11/02/2006 11/01/2012

Included observations: 2192 after adjustments

Convergence achieved after 14 iterations

Variance backcast: ON

GARCH = C(1) + C(2)*RESID(-1)^2 + C(3)*GARCH(-1) Coefficient Std. Error z-Statistic Prob. Variance Equation

C 7.43E-08 2.35E-08 3.162019 0.0016

RESID(-1)^2 0.037617 0.004059 9.267759 0.0000

GARCH(-1) 0.958521 0.004579 209.3525 0.0000

R-squared -0.000274 Mean dependent var -7.65E-05

Adjusted R-squared -0.001188 S.D. dependent var 0.004619

S.E. of regression 0.004622 Akaike info criterion -8.267514

Sum squared resid 0.046755 Schwarz criterion -8.259724

Log likelihood 9064.196 Durbin-Watson stat 1.354166

g

Dependent Variable: EUR

Method: ML ARCH

Date: 11/17/12 Time: 21:00

Sample (adjusted): 11/02/2006 11/01/2012




GARCH = C(1) + C(2)*RESID(-1)^2 + C(3)*GARCH(-1) Coefficient Std. Error z-Statistic Prob.

C 4.60E-08 1.59E-08 2.896032 0.0038

RESID(-1)^2 0.029049 0.003060 9.492336 0.0000

GARCH(-1) 0.969440 0.002609 371.5709 0.0000

R-squared -0.000003 Mean dependent var 8.85E-06





Dependent Variable: CAD

Method: ML - ARCH

Date: 11/17/12 Time: 21:06

Sample (adjusted): 11/02/2006 11/01/2012





C 1.07E-07 3.01E-08 3.548604 0.0004

RESID(-1)^2 0.045261 0.003677 12.30889 0.0000

GARCH(-1) 0.950882 0.003923 242.3588 0.0000






h

Dependent Variable: AUD

Method: ML - ARCH

Date: 11/17/12 Time: 21:11

Sample (adjusted): 11/02/2006 11/01/2012





C 3.38E-07 5.28E-08 6.402043 0.0000

RESID(-1)^2 0.057847 0.004896 11.81637 0.0000

GARCH(-1) 0.934688 0.005059 184.7465 0.0000

R-squared -0.000364 Mean dependent var 0.000135





Dependent Variable: CHF

Method: ML - ARCH

Date: 11/17/12 Time: 21:15

Sample (adjusted): 11/02/2006 11/01/2012





C 1.04E-07 3.15E-08 3.302102 0.0010

RESID(-1)^2 0.041539 0.003752 11.07152 0.0000

GARCH(-1) 0.955365 0.004093 233.3945 0.0000






i

Dependent Variable: NZD

Method: ML - ARCH

Date: 11/17/12 Time: 21:20

Sample (adjusted): 11/02/2006 11/01/2012





C 3.20E-07 6.72E-08 4.757645 0.0000

RESID(-1)^2 0.039802 0.003669 10.84727 0.0000

GARCH(-1) 0.953907 0.003806 250.6229 0.0000






Dependent Variable: JPY

Method: ML - ARCH

Date: 11/17/12 Time: 21:17

Sample (adjusted): 11/02/2006 11/01/2012





C 1.09E-06 1.31E-07 8.362190 0.0000

RESID(-1)^2 0.047718 0.004875 9.787827 0.0000

GARCH(-1) 0.921728 0.007483 123.1766 0.0000







[nh] detai ueh500 2012

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