eddie: a genetic programming tool for financial … lecture2.pdf29 november 2004 all rights...
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29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
:
A G
enet
ic P
rog
ram
min
g T
oo
l
for
Fin
anci
al F
ore
cast
ing
Ed
war
d T
san
g
Univ
ersi
ty o
f E
ssex
ED
DIE
= E
ED
DIE
= E
volu
tionar
yv
olu
tionar
yDD
yn
amic
yn
amic
DDat
aat
aII n
ves
tmen
tnves
tmen
tEE
val
uat
or
val
uat
or
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Sourc
e: S
har
esco
pe,
UK
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
gS
ou
rce:
Sh
ares
cope,
UK
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
Res
earc
h A
gen
da
Su
pp
ose
yo
ur
exp
ert
tell
s y
ou
th
at
–P
rice
-ear
nin
g r
atio
–1
2 o
r 50-d
ays
movin
g a
ver
age
–In
tere
st r
ate
–…
.
are
rele
van
t to
fu
ture
pri
ce o
f F
TS
E-1
00
Ho
w w
ou
ld y
ou
act
ual
ly u
se t
hem
to
fore
cast
?
Go
al:
add
val
ue
to y
ou
r ex
per
t k
no
wle
dg
e
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Eff
icie
nt
Mar
ket
Hy
po
thes
is (
EM
H)
Fin
anci
al a
sset
s (e
.g.
shar
es)
pri
cin
g:
–A
ll a
vai
lable
info
rmat
ion i
s dis
counte
d
If E
MH
ho
lds,
fo
reca
stin
g i
s im
po
ssib
le
–R
andom
wal
k t
heo
ry
Ass
um
pti
on
s:
–E
ffic
ient
mar
ket
s
–P
erfe
ct i
nfo
rmat
ion f
low
–R
atio
nal
tra
der
s
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Do
es t
he
EM
H H
old
?
It h
old
s fo
r th
e lo
ng
ter
m
“Fat
Tail
” o
bse
rvat
ion
:
–b
ig c
han
ges
today
oft
en f
oll
ow
ed b
y b
ig c
han
ges
(eit
her
+ o
r –)
tom
orr
ow
Ho
w f
ast
can
on
e ad
just
ass
et p
rice
s g
iven
a
new
pie
ce o
f in
form
atio
n?
–F
aste
r m
achin
es c
erta
inly
hel
p
–S
o s
hould
fas
ter
algori
thm
s
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
/ F
GP
Ov
erv
iew
ED
DIE
/ F
GP
lea
rns
from
pas
t his
tory
–U
sing G
enet
ic P
rogra
mm
ing
It g
ener
ates
dec
isio
n t
rees
–W
hic
h a
llow
s it
to e
xpla
init
s re
com
men
dat
ions
Use
d l
earn
ed r
ule
s to
answ
er q
ues
tions
such
as:
–W
ill
pri
ces
rise
by
4%
wit
hin
the
nex
t 21 d
ays?
It w
ork
s w
ith
dom
ain
exp
erts
on
–w
hat
featu
res
are
rele
van
t?
–ar
e th
e ru
les
gen
erat
ed r
easo
na
ble
?
Jam
es B
utle
r
ED
DIE
ED
DIE
= E
= E
volu
tionar
yvolu
tionar
yDD
ynam
icynam
icDD
ata
ata
II nves
tmen
tnves
tmen
tEE
val
uat
or
val
uat
or
FG
PF
GP
==FF
inan
cial
inan
cial
GGen
etic
enet
icPP
rog
ram
min
gro
gra
mm
ing
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Wo
rkin
g w
ith
Ex
per
ts
ED
DIE
is
no
t d
esig
ned
to
rep
lace
exp
erts
–It
is
des
igned
to w
ork
wit
hex
per
ts
GP
is
on
ly a
to
ol
–it
nee
ds
exper
t in
put
to b
e ef
fect
ive
Ex
per
ts c
han
nel
kn
ow
led
ge
into
ED
DIE
:
–b
y s
ugges
ting w
hat
fac
tors
are
rel
evan
t
–b
y e
val
uat
ion o
f th
e ru
les
gen
erat
ed
ED
DIE
ad
ds
val
ue
exp
ert
inp
ut
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Exper
t K
now
ledge
in E
DD
IE
Fin
ancia
l E
xpert
Fin
ancia
l E
xpert
Genetic D
ecis
ion T
ree
(GD
T)
Genetic D
ecis
ion T
ree
(GD
T)
ED
DIE
ED
DIE
3. A
ppro
val /
rej
ectio
n
1. S
ugge
stio
n
of in
dica
tors
2. O
utpu
t
Tra
inin
g D
ata
Tra
inin
g D
ata
Eff
ecti
ve
chan
nel
ing o
f ex
per
t know
ledge
into
ED
DIE
is t
he
key
to s
ucc
ess
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Tec
hn
ical
Det
ails
Insi
de
ED
DIE
/ F
GP
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
An
Ex
amp
le D
ecis
ion
Tre
e
No
Has
X’s
pric
e fa
llen
by
6% s
ince
yes
terd
ay?
Has
X’s
pric
e fa
llen
by
6% s
ince
yes
terd
ay?
Yes
Buy
Buy
Yes
No
No
Act
ion
No
Act
ion
Sel
lS
ell
Yes
Sel
lS
ell
No
No
Act
ion
No
Act
ion
Yes
Has
X’s
pric
e ris
en b
y
5% s
ince
a w
eek
ago?
Has
X’s
pric
e ris
en b
y
5% s
ince
a w
eek
ago?
No
Is X
’s p
rice
14-d
ays
mov
ing
aver
age?
Is X
’s p
rice
14-d
ays
mov
ing
aver
age?
Is X
’s P
/E r
atio
low
er th
an th
e
indu
stry
ave
rage
by
20%
?
Is X
’s P
/E r
atio
low
er th
an th
e
indu
stry
ave
rage
by
20%
?
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Synta
x o
f G
DT
sin
ED
DIE
-2
<T
ree>
::=
“If-
then
-els
e” <
Con
ditio
n> <
Tre
e> <
Tre
e> |
Dec
isio
n
<C
ondi
tion>
::=
<C
ondi
tion>
"A
nd"
<C
ondi
tion>
|
<C
ondi
tion>
"O
r" <
Con
ditio
n>
|
"Not
"
<C
ondi
tion>
|
Var
iabl
e<
Rel
atio
nOpe
ratio
n>T
hres
hold
<R
elat
ionO
pera
tion>
::=
">"
|
"<"
| "
="
Var
iabl
eis
an
indi
cato
r / f
eatu
re
Dec
isio
nis
an
inte
ger,
“P
ositi
ve”
or “
Neg
ativ
e” im
plem
ente
d
Thr
esho
ldis
a r
eal n
umbe
r
Ric
her
lan
gu
age
larg
er s
earc
h s
pac
e
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
A t
aste
of
use
r in
pu
t
Def
ine
targ
et:
4%
in
21 d
ays?
0 0 1 1
…..
More
input:
Vola
t-
ilit
y
50
52
53
51
…..
Exper
t
adds:
50 d
ays
m.a
.
80
82
83
82
…..
Giv
en
Dai
ly
closi
ng
90
99
87
82
…..
…..
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
ad
ds
val
ue
to u
ser
inp
ut
Use
r in
pu
ts i
nd
ica
tors
–e.
g. m
ovin
g a
ver
age,
vola
tili
ty, pre
dic
atio
ns
ED
DIE
mak
es s
elec
tors
–e.
g. “5
0 d
ays
movin
g a
ver
age
> 8
9.7
6”
ED
DIE
co
mb
ines
sel
ecto
rs i
nto
tre
es
–b
y d
isco
ver
ing i
nte
ract
ions
bet
wee
n s
elec
tors
Fin
din
g t
hre
sho
lds
(e.g
. 8
9.7
6)
and
in
tera
ctio
ns
by
hu
man
ex
per
ts i
s la
bo
rio
us
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Res
earc
h M
eth
od
olo
gy
Co
nce
ntr
ate
on
pre
dic
tin
g:
G=
“w
ill
pri
ces
go u
p/d
ow
n b
y r
% w
ithin
the
nex
tn
day
s?”
To
ev
alu
ate
ED
DIE
, ch
oo
se r
and
nsu
ch
that
50
% o
f th
e d
ays
ach
iev
e G
–P
erfo
rman
ce a
gai
nst
ran
dom
dec
isio
ns
–A
lso c
om
par
ed a
gai
nst
ID
3 /
C4.5
Mea
sure
pre
dic
tio
n a
ccu
racy
–R
eturn
on i
nves
tmen
t al
so u
sed f
or
refe
rence
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Tes
tin
g o
f E
DD
IE
S&
P 5
00
In
dex
, 1
96
3 t
o 1
97
4
Do
w J
on
es I
nd
ust
rial
Av
erag
e In
dex
Co
mb
inin
g e
xp
ert
pre
dic
tio
ns
on
Hen
gS
eng
Ind
ex
Sh
ares
: IB
M,
HS
BC
, B
AA
, B
HP
, A
NZ
, 1
99
1
to 2
00
0
UK
han
dic
ap h
ors
e ra
ces
19
93
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
on
S&
P 5
00
dai
ly c
lose
Tra
ined
: 2
/4/6
3 t
o 2
/7/7
0 (
18
00
day
s)
Tes
ted
:6/7
/70
to
25
/1/7
4 (
90
0 d
ays)
Tar
get
: “r
ise
of
4%
wit
hin
63
da
ys”
Inp
ut:
tex
tbo
ok
tec
hn
ical
in
dic
ato
rs
–e.
g.n
day
s m
ovin
g a
ver
ages
/ m
in/
max
pri
ces
Res
ult
: 5
4%
acc
ura
cy, 4
3%
an
nu
al r
etu
rnR
efer
ence
:Soft
ware
, P
ract
ice
& E
xper
ience
, 28(1
0)
1998
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Per
form
ance
Mea
sure
sP
redi
ctio
nsR
ealit
y
Neg
ativ
e
Pos
itive
Pos
itive
Fal
se
Pos
itive
Tru
e
Pos
itive
Neg
ativ
e
Tru
e
Neg
ativ
e
Fal
se
Neg
ativ
e
Rat
e of
corr
ectn
ess
= (
TN
+ T
P)
Tota
l
Rat
e of
fail
ure
= F
P
(FP
+ T
P)
= 1
–pre
cisi
on
Rat
e of
mis
sing c
han
ces
= F
N
(FN
+ T
P)=
1 –
reca
ll
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
on
IB
M 1
99
1-1
99
7
60%
of
reco
mm
endat
ions
corr
ect
–w
her
e o
pp
ort
un
itie
s o
ccu
r in
45
% o
f th
e d
ays
IBM
Tra
inin
g P
eriod (
1991.1
0.3
0-1
995.1
2.2
7)
RC
61.4
%0
1O
pport
.:42.3
%
RM
C89.1
%654
10
0664
RF
15.9
%434
53
1487
1088
63
5%
1151
IBM
Ove
r Test
Period (
1995.1
2.2
8-1
997.0
3.0
5)
RC
56.5
%0
1O
pport
.:45.0
%
RM
C90.0
%104
60
110
RF
40.0
%81
91
90
AR
210.0
%185
15
8%
200
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
FG
P2
on
HS
BC
19
96
-20
00
–N
o r
ecom
men
dat
ions
mad
e
HS
BA
Tra
inin
g12/0
3/9
6to
28/5
/1999
RC
54.8
%0
1O
pport
.:52.1
%
RM
C83.8
%389
13
0402
RF
15.5
%366
71
1437
755
84
10%
839
HS
BA
Testing
31/5
/1999
to03/0
3/0
0
RC
59.0
%0
1O
pport
.:41.0
%
RM
C100.0
%118
00
118
RF
N.A
.82
01
82
200
00%
200
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Imp
rov
ing
Pre
cisi
on
Red
uci
ng
Rat
e o
f F
ailu
re
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Red
uci
ng
Rat
e o
f F
ailu
re (
RF
)
Neg
ativ
e
Tru
e
Neg
ativ
e
Fal
se
Neg
ativ
e
Pre
dict
ions P
ositi
ve
Fal
se
Pos
itive
Tru
e
Pos
itive
Rea
lity
Neg
ativ
e
Pos
itive
RF
= F
P
(FP
+ T
P)
= 1
–pre
cisi
on
RM
C =
FN
(F
N +
TP
)=
1 –
reca
ll
Red
uce
RF
at
the
cost
of
RM
C
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Jin
Li
FG
P
FG
P:
Co
nst
rain
ed F
itn
ess
Const
rain
ts c
an h
elp g
uid
ing t
he
sear
ch
Fit
nes
s =
wrc
RC
’w
rmc
RM
Cw
rfR
F
RC
’ =
RC
if P
+
[Min
, M
ax]
0
oth
erw
ise
Neg
ativ
e
Tru
e
Neg
ativ
e
Fal
se
Neg
ativ
e
Pos
itive
Fal
se
Pos
itive
Tru
e
Pos
itive
One
can a
dju
st M
in a
nd M
ax t
o
refl
ect
mar
ket
expec
tati
on
(poss
ibly
fro
m t
rain
ing),
or
risk
pre
fere
nce
Cau
tious
Low
Max
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Red
uci
ng
RF
Des
irab
le t
o r
edu
ce R
ate
of
Fa
ilu
re–
Mis
sing o
pport
unit
ies
may
be
more
acc
epta
ble
th
an l
osi
ng m
oney
Ou
r ap
pro
ach
:–
Augm
ent
fitn
ess
wit
h c
onst
rain
ts
–T
ighte
r co
nst
rain
ts m
eans
low
er R
F
–E
ven
if
low
er R
F
more
mis
sed c
han
ces
Ou
r g
oal
:–
All
ow
one
to t
une
RF
to o
ne’
s pre
fere
nce
–w
ithout
affe
ctin
g o
ver
all
Rat
e of
Corr
ectn
ess
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
FG
P-2
on
IB
M 1
99
1-1
99
7
•W
ith l
ow
rat
e of
fail
ure
spec
ifie
d
•R
esult
s ar
e m
ore
rel
iable
Constr
ain
ed fitness function:
IBM
Tra
inin
g P
eriod (
1991.1
0.3
0-1
995.1
2.2
7)
RC
60.5
%0
1O
pport
.:42.3
%
RM
C84.6
%621
43
0664
RF
36.4
%412
75
1487
1033
118
10%
1151
Constr
ain
ed fitness function:
IBM
Test
Period (
1995.1
2.2
8-1
997.0
3.0
5)
RC
59.0
%0
145.0
%
RM
C87.8
%107
30
110
RF
21.4
%79
11
190
AR
511.0
%186
14
7%
200
Genera
l fit
ness function:
IBM
Ove
r Test
Period (
1995.1
2.2
8-1
997.0
3.0
5)
RC
56.5
%0
1O
pport
.:45.0
%
RM
C90.0
%104
60
110
RF
40.0
%81
91
90
AR
210.0
%185
15
8%
200
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
DJ
IA In
de
x C
los
ing
Pri
ce
s
45
0
50
0
55
0
60
0
65
0
70
0
75
0
80
0
85
0
90
0
95
0
10
00
10
50
11
00
0200
400
600
800
1000
1200
1400
1600
1800
2000
2200
2400
2600
2800
3000
Tra
din
g D
ays
Index Price
Tra
inin
g P
eri
od
Tes
t P
eri
od
Dow
n
Sid
eway
Up
FG
P-2
on
DJI
A
Dat
a
–T
rain
ing
: 1
,90
0 d
ays
07
/04
/19
69
to
11
/10
/19
76
–T
esti
ng
: 1
,13
5 d
ays
12
/10
/19
76
to
09
/04
/19
81
–T
arg
et:
“ris
e of
4%
wit
hin
63 d
ays
”
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Eff
ect
of
const
rain
ts o
n F
GP
-2
0.0
0
0.5
0
1.0
0
1.5
0
2.0
0
2.5
0
3.0
0
05_10
10_15
15-2
020-3
535-5
050-6
5
Co
nstr
ain
ed
ne
ss
Rate (%)
0100
200
300
400
500
600
700
# of + signals
RF
AA
RR
RC
RM
C# o
f S
IGN
ALS
Obse
rvat
ion:
RM
C c
an b
e tr
aded
for
RF
wit
hout
signif
ican
tly a
ffec
ting R
C
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Ou
r F
GP
Ex
per
ien
ce
Pat
tern
s ex
ist
–W
ould
they
rep
eat
them
selv
es i
n t
he
futu
re?
(EM
H d
ebat
ed f
or
dec
ades
)
ED
DIE
has
fo
un
d p
atte
rns
–N
ot
in e
ver
y s
erie
s
(we
don’t
nee
d t
o i
nves
t in
ever
y i
ndex
/ s
har
e)
ED
DIE
ex
ten
din
g u
ser’
s ca
pab
ilit
y
–an
d g
ive
its
use
r an
edge
over
inves
tors
of
the
sam
e ca
liber
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Hig
h F
requ
ency
Dat
a:
Exam
ple
of
an O
rder
Book
Pri
ceV
olu
me
Ord
ers
Sel
ler
43
.86
2,0
00
1
Sel
ler
33
.85
10
,00
05
Sel
ler
23
.84
5,0
00
1
Sel
ler
13
.83
1,0
00
1
Buyer
13
.82
6,0
00
3
Buyer
23
.81
8,0
00
3
Buyer
33
.80
5,0
00
1
Buyer
43
.79
17
,00
03
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
in
Arb
itra
ge,
His
tori
cal
Note
1996:
FG
P
( Fin
anci
alF
inan
cial
GGen
etic
enet
icPP
rog
ram
min
g)
rog
ram
min
g)
Jin
Li
1995:
ED
DIE
( EEvolu
tionar
yvolu
tionar
yDD
ynam
icynam
icDD
ata
ata
II nves
tmen
tnves
tmen
tEE
val
uat
or)
val
uat
or)
Jam
es B
utle
rE
dwar
d T
sang
2000:
FG
P+
Arb
itra
ge
She
ri M
arko
seH
akan
Er
Arb
itra
ge
Res
earc
h
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Arb
itra
ge
Op
po
rtu
nit
ies
Futu
res
are
obli
gat
ions
to b
uy o
r se
ll a
t ce
rtai
n p
rice
s
Opti
ons
are
rights
to b
uy a
t a
cert
ain p
rice
If t
hey
are
not
alig
ned
, one
can m
ake
risk
-fre
e pro
fits
–S
uch
opport
unit
ies
should
not
exis
t
–B
ut
they
do i
n L
ondon
Opti
on r
ight:
£10
Futu
re P
rice
: £11
Opti
on p
rice
: £0.5
{
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
in
Arb
itra
ge
Neg
ativ
e
4,90
0
96
Pos
itive
0 4
Typic
al a
rbit
rage
resu
lt
Arb
itra
ge
op
po
rtu
nit
ies
fou
nd
–T
hey
should
n’t
exis
t?
–T
hey
exis
t fo
r 12-4
5 s
econds
ED
DIE
to
pre
dic
t ar
bit
rag
e
–1
5 m
inute
s in
advan
ce
–F
ind c
lear
opport
unit
ies
only
Hu
man
ex
per
tise
nee
ded
–9
month
s dat
a pre
pro
cess
ing
–O
ver
10 d
ata
set
revis
ions
Pro
fita
ble
arb
itra
ge
opport
unit
ies
are
rare
;
Can
’t a
fford
to m
iss
too m
any
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
Art
ific
ial
Mar
ket
8000
9000
10000
11000
12000
13000
14000
15000
02/0
1/02 02
/03/0
2 02/0
5/02 02
/07/0
2 02/0
9/02 02
/11/0
2 02/0
1/03 02
/03/0
3 02/0
5/03 02
/07/0
3 02/0
9/03 02
/11/0
3 02/0
1/04 02
/03/0
4 02/0
5/04 02
/07/0
4 02/0
9/04
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
as
Inte
llig
ent
Ag
ent
Ser
afin
Mar
tinez
ED
DIE
Red
Q
Let
art
ific
ial
agen
ts f
or
a
mar
ket
–T
ech
nic
al t
rad
ers
(ED
DIE
)
–F
un
dam
enta
l tr
ader
s
(Eco
nom
ists
)
–N
ois
e tr
ader
s
How
would
the
pri
ces
look l
ike?
Under
what
condit
ions
wil
l th
ey p
roduce
rea
l
mar
ket
sty
lus?
Do
w J
on
es
In
du
str
ial In
de
x
7000
7500
8000
8500
9000
9500
10000
10500
11000
02/0
1/03 02
/03/
03 02/0
5/03 02
/07/
0302
/09/
03 02/1
1/03 02
/01/
04 02/0
3/04 02
/05/
04 02/0
7/04
02/0
9/04
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
The
Red
Quee
n E
ffec
t
Pow
er L
aw w
ealt
h d
istr
ibuti
on
–T
he
wea
kes
t m
ust
re-
trai
n
them
selv
es
Red
quee
n e
ffec
t
–Y
ou h
ave
to r
un a
s fa
st a
s you c
an
to s
tay i
n t
he
sam
e pla
ce
ED
DIE
is
use
d f
or
re-t
rain
ing
She
ri M
arko
se
Red
Que
en
Ser
afin
Mar
tinez
ED
DIE
Red
Q
00.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
in
Bu
sin
ess
Fro
m r
esea
rch
to
pra
ctic
e:
Su
rfin
g o
ne
step
ah
ead
of
each
wav
e
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Wh
at c
an E
DD
IE d
o f
or
yo
u?
If i
t ch
ang
es 5
0-5
0 c
han
ces
to 5
5-4
5
–in
your
favour
–y
ou m
ust
be
bet
ter
off
in t
he
long r
un…
It h
elp
s y
ou
to
bea
t o
ther
in
ves
tors
of
the
sam
e ca
lib
re
–It
pro
vid
es a
n e
xtr
a ex
per
t opin
ion
–If
all
your
exper
ts g
ive
you t
he
sam
e opin
ion, you
hav
e bet
ter
chan
ce t
o s
ucc
eed
It w
ork
s d
ay a
nd
nig
ht,
yo
u c
an’t
…
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
ED
DIE
/FG
P i
s n
o m
agic
A t
oo
l is
use
ful
wh
en..
.
–it
can
do s
om
ethin
g g
ood, an
d
–w
e know
how
to u
se i
t, a
nd
–w
e know
its
lim
itat
ions
ED
DIE
/ F
GP
is
such
a t
oo
l
–N
o e
xper
t in
put,
no u
sefu
l fo
reca
st
(It
only
adds
val
ue
to e
xper
t in
put)
–It
can
only
fin
d p
atte
rns
that
exis
t
(No p
oin
t as
kin
g i
t to
pre
dic
t th
e lo
tter
y)
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Do
n’t
ex
pec
t to
see
…
Mir
acle
s –
–w
e ca
n’t
pre
dic
t th
e unpre
dic
table
!
Pre
dic
tio
n o
f ev
ery
thin
g
–M
ay n
ot
find p
atte
rns
for
the
futu
re
•E
.g. pat
tern
s fo
und i
n I
BM
/BA
A, but
not
HS
BC
•S
o n
o p
osi
tive
acti
ons
reco
mm
ended
Fan
cy i
nte
rfac
e
–A
t th
e m
om
ent,
we
conce
ntr
ate
to m
ake
ED
DIE
pre
dic
t acc
ura
tely
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Curr
ent
Res
earc
h
ED
DIE
fo
r A
rbit
rag
e–
Spot,
opti
on a
nd f
utu
re p
rice
s don’t
alw
ays
synch
roniz
e
–H
ence
one
can m
ake
risk
-fre
e re
turn
?
ED
DIE
for
Fore
cast
ing
–W
hen
to s
ell?
How
to c
om
bin
e si
gnal
s?
–W
hat
is
the
retu
rn i
n r
eali
ty?
GP
for
model
ling v
ola
tili
ty–
coef
fici
ents
fit
ting f
or
GA
RC
H-l
ike
funct
ions
–D
isco
ver
ing n
ew f
unct
ions
form
s?
GP
for
mar
ket
under
stan
din
g–
Lea
rnin
g a
gen
ts f
orm
art
ific
ial
mar
ket
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
The
Com
puta
tiona
l Fin
ance
Res
earc
h T
eam
Jam
es B
utle
r
ED
DIE
Jin
Li
FG
P
Tun
gL
Lau
Ear
ly T
ools
Edw
ard
Tsa
ng
ED
DIE
/ G
P
Giu
lia Io
ri
Vol
atili
ty
She
ri M
arko
se
Red
Que
en
Abd
el S
alhi
Gen
etic
Pro
g.
Hak
anE
r
Arb
itrag
e
Ric
card
oP
oli
Gen
etic
Pro
g.M
aria
Fas
li
Age
nt T
ech.
John
Gan
Dat
a m
inin
g
Abh
inay
Mut
hoo
Gam
e T
heor
y
Ser
afin
Mar
tinez
ED
DIE
Red
Q
Nan
linJi
n
Bar
gain
ing
Bili
ana
Ale
xand
rova
-
Kab
adjo
va
Sm
all w
orld
Alm
a G
arci
a
For
ecas
ting
29
No
vem
ber
20
04
All
Rig
hts
Res
erv
ed,
Ed
war
d T
san
g
Qu
esti
on
s, D
iscu
ssio
n