November 2008 Financial Fuzzy BasedSystems · Three line break The three line break chart is similar in concept to point and figure charts. The decision criteria for determining "reversals"

1

Financial Informatics –XII:

Financial Fuzzy Logic Based

Systems

1

Khurshid Ahmad,

Professor of Computer Science,

Department of Computer Science

Trinity College,

Dublin-2, IRELAND

November 19th, 2008.

https://www.cs.tcd.ie/Khurshid.A

hmad/T

each

ing.htm

l

2

Fuzzy Financial Systems

http://w

ww.stree

tdirec

tory.com/travel_guide/36574/investm

ent/candlestick_ch

arting___a_

pee

k_into_market_psy

chology.htm

l

The beh

aviour of th

e stakeh

older

s in a m

ark

et is an

intere

sting aven

ue of study. T

he re

action to change is one

of th

e key

are

as of intere

st here; the manner

in w

hich

change is anticipated varies fro

m per

son to per

son, but

ther

e are

some gen

eraliza

tions are

beg

inning to appea

r.

For instance, investors appea

r to have heu

ristics that

under

line their beh

aviour:

(1)IF

there

is gre

ate

r th

an a

vera

ge p

rice

movem

ent on the (re

vers

al) d

ay

TH

EN

I look for th

e p

rice

to e

xceed its n

orm

al daily

price

range

[…].

(2)IF

a S

tock p

rice that is h

eavily o

verb

ought or overs

old

TH

EN

I look for th

e p

rice

to a

ccele

rate

away[..]

3


http://w

ww.stree

tdirec


ent/candlestick_ch

arting___a_

pee

k_into_market_psy

chology.htm

l

Now, when

we wish to know how a stock, co

mmodity, cu

rrency

, or an entire

market is

beh

aving, we tend to find the ‘price’

of the instru

ment. Usu

ally w

e get a single number

for an entire

period. trading per

iod. Typically, th

e price quoted for th

e instru

men

t at th

e

end of a tra

ding (fractional) hour, day, week and so on

4


http://w

ww.stree

tdirec


ent/candlestick_ch

arting___a_

pee

k_into_market_psy

chology.htm

l

But, in rea

lity,

the price

s are

changing

during a

trading period,

going thro

ugh

highs and lows

–re

versal are

quite co

mmon

within a

per

iod

5


http://finan

ce.google.com/finan

ce?client=ob&q=IN

DEXDJX

:DJI

But, in rea

lity,

the price

s are

changing

during a

trading period,

going thro

ugh

highs and lows

–re

versal are

quite co

mmon

within a

per

iod.

6

Fuzzy Financial Systems:

Observing change through candlesticks

Chiung-H

on Leo

n Lee, Alan Liu, and W

en-S

ung C

hen

(2006). ‘Pattern D

isco

very of Fuzz

y Tim

e Series for Finan

cial Prediction’. IE

EE Transa

ction on D

ata and K

nowledge

Engineering. V

ol18 (No. 5), pp 613-625.

The behaviour of financial

instruments over a period of time

shows that there is an inherent

fuzziness in this behaviour. T

he

behaviour shows characteristic

patterns –captured by the so-called

candle

stic

k p

attern

s used to display

the full range of behaviour during

the period of time. T

he range

includes the value of the instrument

at the beginning and end of the

trading period (called o

pen and

clo

se), and the highest and the lowest

values during trading (called h

igh

and low).

Usu

ally, only the closing value of the

instrument is cited.

Closing

Value

Bar

Chart

Can

dlestick

If

open

value is greater than closing value

then

paint the body w

hite

If

open

value is smaller than closing value

then

paint the body black

Ifopen

value is appro

x. eq

ual to closing

then

put hatched

lines in the body

7


Observing change through line breaks

Three line break

The three line break

chart is

similar in concept to point

and figure charts. The

decision criteria for

determining "reversals" are

somew

hat different. The

three-line break

chart looks

like a series of rising and

falling lines of varying

heights. Using closing price

s

(or highs an

d lows), a new

rising line is drawn if the

previous high is ex

ceed

ed. A

new

falling line is drawn if

the price

hits a new

low.

http://w

ww.linnsoft.com/tour/threeL

ineB

reak

Chart.htm

Daily FOREX EUR=,22

30

/11

/20

07

- 3

0/1

0/2

00

8 (

GM

T)

3L

nB

rk,

FO

RE

X E

UR

=,2

2

27

/10

/20

08

, 1

.26

22

, 1

.24

66

Pri

ce

US

D

.12

34

1.2

6

1.2

7

1.2

8

1.2

9

1.3

1.3

1

1.3

2

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1.5

1

1.5

2

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1.5

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5

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7

1.5

8

1.3

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1

30

/11

/20

07

19

/12

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28

/12

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14

/01

/20

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30

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/03

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14

/03

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26

/03

/20

08

07

/05

/20

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11

/08

/20

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01

/09

/20

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/09

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03

/10

/20

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20

/10

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08

27

/10

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08

27

/10

/20

08

‘Three line break charts and T

echnical Analysis

8


EykeHüllermeier

(2008). Fuzz

y sets in m

achine learning and data mining. Journ

al of Applied

Soft C

omputing (forthco

ming).

doi:10.1016/j.aso

c.2008.01.004

Data m

ining per

haps is one of th

e most important are

a

wher

e fu

zzy logic based system

s will see co

nsider

able

usa

ge.

Tra

ditionally, business analysts have per

form

ed the task

of ex

tracting usefu

l inform

ationfrom record

ed data, but

the increa

sing volume of data in m

oder

n business and

science

calls for co

mputer-based appro

ach

es.

Data m

ining involves the applica

tion of intelligen

t

pro

gra

ms for ex

tracting inform

ation fro

m record

ed data.

9


Recognizing patterns of change

Daily FOREX EUR=,22

02

/09

/20

08

- 2

4/1

1/2

00

8 (

GM

T)

Up

tre

nd

Do

wn

tre

nd

Cn

dl,

FO

RE

X E

UR

=,2

2,

Bid

15

/10

/20

08

, 1

.36

2,

1.3

68

5,

1.3

45

3,

1.3

46

Pri

ce

US

D

.12

34

1.2

6

1.2

9

1.3

2

1.3

5

1.3

8

1.4

1

1.4

4

1.4

85

5

08

15

22

29

06

13

20

27

03

10

17

24

September 2008

October 2008

November 2008

We

d 1

5/1

0/2

00

8

Candlesticks and T

echnical Analysis (C

ompressed over a day)

We ca

n use the

candlestick

patterns –a

collection of

candle stick

s-

to speculate

about th

e

reversals (or

otherwise) of

the instru

men

t

over a given

period of time.

10


Recognizing patterns of change

10 Minutes FOREX EUR=,22

01

:00

19

/11

/20

08

- 1

0:3

0 1

9/1

1/2

00

8 (

GM

T)

Cn

dl,

FO

RE

X E

UR

=,2

2,

Bid

10

:00

19

/11

/20

08

, 1

.26

06

, 1

.26

1,

1.2

59

8,

1.2

60

6

Pri

ce

US

D

.12

34

1.2

59

1

1.2

59

4

1.2

59

7

1.26

1.2

60

3

1.2

60

6

1.2

60

9

1.2

61

2

1.2

61

5

1.2

61

8

1.2

62

1

1.2

62

4

1.2

62

7

1.263

1.2

63

3

1.2

63

6

1.2

63

9

1.2

64

2

1.2

64

5

1.2

59

8

01

:10

01

:40

02

:10

02

:40

03

:10

03

:40

04

:10

04

:40

05

:10

05

:40

06

:10

06

:40

07

:10

07

:40

08

:10

08

:40

09

:10

09

:40

10

:10

19 November 2008

10

:00

We

d 1

9/1

1/2

00

8

Candlesticks and T

echnical Analysis (10 m

inute compression)

We can use the

candlestick

patterns –a

collection of

candle sticks-

to

speculate about

the reversals (or

otherw

ise) of the

instrument over

a given period of

time:will our

stra

tegy m

ay

change

dep

ending our

time horizo

ns?

11


On candlesticks

http://stock

charts.com/sch

ool/doku.php?id=ch

art_school:ch

art_an

alysis:introduction_to_ca

ndlesticks

Short body can

dlesticks indicate

little or no chan

ge in price and

perhap

s co

nso

lidation.

Long body can

dlesticks indicate

intense buying and selling

pressure

Patterns

Description

12


More on candlestick patterns

http://stock

charts.com/sch

ool/doku.php?id=ch

art_school:ch

art_an


ndlesticks

Rising Three Methods: A

bullish

continuation pattern in w

hich a long w

hite

body is followed

by three sm

all body day

s,

each

fully contained

within the range of the

high and low of the first day

. The fifth day

closes at a new

high.

Aban

doned

Bab

y: A rare reversal pattern

characterized by a gap

followed

by a D

oji,

which is then

followed

by another gap

in the

opposite direction.

Patterns

Description

13



http://stock

charts.com/sch

ool/doku.php?id=ch

art_school:ch

art_an


ndlesticks

Prior Trend R

eversal

Bullish rev

ersals req

uire a preceding downtren

d and bearish rev

ersals

require a prior uptren

d. The direction of the tren

d can

be determined

using

tren

d lines, moving averag

es, peak/trough analysis or other asp

ects of

tech

nical analysis. A

downtren

d m

ight ex

ist as long as the secu

rity w

as

trad

ing below its down trend line, below its previous reaction highor

below a specific m

oving averag

e. The length and duration w

ill dep

end on

individual preferences.

14



http://stock

charts.com/sch

ool/doku.php?id=ch

art_school:ch

art_an


ndlesticks

Long Shadow R

eversal

There are tw

o pairs of single can

dlestick rev

ersal patterns mad

eup of a

small real body, one long shad

ow and one short or non-existent shad

ow.

15



Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen (2006). ‘Pattern D

isco

very of Fuzzy Tim

e Series for Finan


EE Tra

nsa

ction on D

ata

and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

We see a variety of patterns in the beh

aviour of prices

(open

/high/low/close) over a period of time. The pattternshav

e a

characteristic shap

e: Bullish engulfing, shooting star

16


Systems for recognizing patterns?

•There is a belief that the study of patterns for

iden

tifying reversa

ls and turning points can be

conducted

using candlestick patterns, line breaks and

so on.

•These methods are em

pirical and perhap

s throw

some light on investor psy

chology.

•The em

phasis here is on w

hat the

investors/traders/brokers do and need, rather than

what the modelers an

d sch

olars think how the markets

and peo

ple beh

ave.

17


Systems for recognizing patterns?

•There is a belief that the study of patterns for

iden

tifying reversa

ls and turning points can be

conducted

using candlestick patterns, line breaks and

so on.

•These methods are em

pirical and perhap

s throw

some light on investor psy

chology.

•The em

phasis here is on w

hat the

investors/traders/brokers do and need, rather than

what the modelers an

d sch

olars think how the markets

and peo

ple beh

ave.

18


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

What is required

is a good knowledge representation

method for representing the knowledge of how to

relate a can

dlestick pattern to the movem

ent of the

instrumen

t/market.

Fuzzy logic based system

s have bee

n recen

tly dev

eloped

for

using candlestick data for acq

uiring and dep

loying

knowledge of financial pre

diction (Lee

, Liu and C

hen

2006).

The ru

les acq

uired

make th

e sy

stem

tra

nsp

arent and the

outp

ut highly visualisa

ble. This is usu

ally not th

e ca

se of

oth

er m

ethods like neu

ral nets, stoch

astic m

odeling.

19


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

The key

notion here is that of a fuzzy tim

e series:

Imprecise data at equally spaced

discrete time points

are modeled

as fuzzy variables.

For individual ca

ndlesticks, T

he ra

ther

imprecise notions of

‘len

gth

’of th

e body

part, le

ngth

of th

e sh

adows (u

pper

and

lower

)are

form

alisedthro

ugh the use of fu

zzy sets and

spec

ifically thro

ugh m

ember

ship functions.

The linguistic variables for length are short, middle,

and long.

20


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For individual ca

ndlesticks, T

he ra

ther

impre

cise notions of ‘len

gth

’of th

e body

part

,

length

of th

e sh

adow

s (u

pper

and low

er)are formalisedth

rough the use of fu

zzy sets and

specifically thro

ugh m

embersh

ip functions.

Heu

ristic N

ote: These functions are described

for the Taiw

anese stock

market in one im

portant sense:

‘the vary

ing percentages of the stock

prices are lim

ited

to 14 percent in the Taiw

anese stock

market’

(Lee, Liu and C

hen

2006:616).

21


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For individual ca

ndlesticks, T

he ra

ther imprecise notions of ‘len

gth

’of th

e body

part

, le

ngth

of th

e

shadows (u

pper

and lower

)are form

alisedthro

ugh the use of fuzzy sets and specifically thro

ugh

membersh

ip functions.

Heuristic Note: These functions are described for the T

aiw

anese stock m

arket

in one important sense: ‘the varying percentages of the stock prices are lim

ited

to 14 percent in the T

aiw

anese stock m

arket’

(Lee, Liu and C

hen 2006:616). So

a a candlestick has definitely has SHORT

length

or bodyif the percentage

change in the instrument was betw

een 0.5 and 1.5; the evidence that the length

was SHORT

when the change w

as 2%

is 0.5, and any change above 2.5%

cannot be regard

ed as SHORT. Sim

ilarly, any change changein the length or

body above 5%

is definitely L

ONG.

22


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

The key

notion here is that of a fuzzy tim

e

series: Im

precise data at equally spac

ed discrete

time points are m

odeled

as fuzzy variables.

Can

dlestick patterns involve more than

two

patterns. It is the relative lengths of these

patterns that result in idiosyncratic patterns.

Linguistic variables are defined

to cap

ture the

essence of the co

mparative nature of the

patterns at the open

ingan

d closing.

23


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For ca

ndlestick patterns that involve more than

two patterns. It is the relative lengths

of these patterns that result in idiosy

ncratic patterns. Linguistic variables are defined

to cap

ture the essence

of the co

mparative nature of the patternsat the open

ingan

d

closing. There are five linguistic variables for open

and close respec

tively: low,

equal_low, eq

ual, equal_highan

d high

‘The related positions of

the open

and close price to

the previous candlestick

line are used to m

odel the

open

style and the close

style.’(ibid:617)

24


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For ca

ndlestick patterns that involve more than

two patterns. It is the relative lengths

of these patterns that result in idiosy

ncratic patterns. Linguistic variables are defined

to cap

ture the essence

of the co

mparative nature of the patternsat the open

ingan

d

closing. There are five linguistic variables for open

and close respec

tively: low,

equal_low, eq

ual, equal_highan

d high

‘The related positions of

the open

and close price to

the previous candlestick

line are used to m

odel the

open

style and the close

style.’(ibid:617)

25


Observing change through candlesticks

Chiung-H

on Leo

n Lee, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE Transa

ction on D

ata and K

nowledge

Engineering. V

ol18 (No. 5), pp 613-625.

The co

lourof th

e body can be

assigned

in relation to their

aggressive beh

aviour (b

ullish)

or

pass

ive beh

aviour

(bea

rish

).

The ca

ndlesticks ca

n be

assigned

the label b

ullish and

bea

rish

. A

nd, hed

ged

in

relation to the quality of

beh

aviour:

NO

RM

AL_BU

LLIS

H,

WEAK_BU

LLIS

H,

STRO

NG

_BU

LLIS

H, or

EXTR

EM

E B

ULLIS

H.

Sim

ilarly for

BEA

RIS

H.

Closing

Value

Bar

Chart

Can

dlestick

If

open

value is greater than closing value

then

the body colouris B

EARIS

H

If

open

value is smaller than closing value

then

the body colouris B

ULLIS

H

Ifopen

value is appro

x. eq

ual to closing

then

then

the variable is CROSS

26


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For candlestick patterns that involve more than

two patterns. W

e also

hav

e to define the deg

ree

of variation betwee

n two can

dlesticks: w

hether the variation showed

increa

se or dec

rease in the

lengths or the body, an

d w

hether or not the increa

se or decrease w

as larg

e, small, norm

al or

extrem

e.

Lee et al’s

prototype used a trading variation divided

into 7 or 8 intervals ranging from the

minim

um chan

ge Im

into a m

aximum chan

ge Im

ax an

d then

creating m

intervals.

u1=[-6,-4]…

……………….

u7=[6,8];

So the set A1 is a set of the

largest decremen

ts together w

ith

some elem

ents of norm

al

decremen

t. Conversely, A7 has

the largest increm

ents and some

elem

ents of norm

alincrem

ents.

27


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

For candlestick patterns that involve more than

two patterns. W

e also

hav

e to define the deg

ree

of variation betwee

n two can

dlesticks: w

hether the variation showed

increa

se or dec

rease in the

lengths or the body, an

d w

hether or not the increa

se or decrease w

as larg

e, small, norm

al or

extrem

e.

Lee et al’s

prototype used a trading variation divided

into 7 or 8 intervals ranging from the

minim

um chan

ge Im

into a m

aximum chan

ge Im

ax an

d then

creating m

intervals.

u1=[-6,-4]…

……………….

u7=[6,8];

So the set A1 is a set of the

largest decremen

ts together w

ith

some elem

ents of norm

al

decremen

t. Conversely, A7 has

the largest increm

ents and some

elem

ents of norm

alincrem

ents.

28


Chiung-H

on Leo

n Lee

and Alan Liu (2006). ‘A Finan

cial D

ecision Supporting System

Based

on Fuzz

y C

andlestick Patterns’. Pro

c. of the

9th Joint Conf.onInform

ation Scien

ces. Paris: Atlan

tis Press. (http://w

ww.atlan

tis-press.com/publica

tions/aisr/jcis-

06/index

_jcis.htm

l?http%3A//www.atlan

tis-press.com/php/pap

er-details.php%3Fid%3D58).

A

candlestick

patter

n for a

fuzzy tim

e

series:

29


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

Lee et al’s

system

computes which of the variation sets

a candlestick pattern belongs to:

30


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

Some of the heu

ristics iden

tified

by Lee et al include:

31


Chiung-H

on Leo

n Lee

, Alan Liu, and W

en-S

ung C

hen


isco

very of Fuzz

y Tim

e Series for Finan


EE

Tra

nsa

ction on D

ata and K

nowledge Enginee

ring. V

ol18 (No. 5), pp 613-625.

An initial ev

aluation of Taiwan

ese Stock

Market data,

used both for training and testing shows en

couraging

resu

lts.

The sy

stem

is reporteely

being used for teaching and

learning.

Documents

November 2008 Financial Fuzzy BasedSystems · Three line break The three line break chart is similar in concept to point and figure charts. The decision criteria for determining "reversals"