Upload
jewel-haynes
View
228
Download
0
Embed Size (px)
Citation preview
Science of x100s in Stock Market IMKBa first order approach
function of Science
= prediction
Data Prediction (=problem) (=solution)
Science
Can we use the methods of science to make predictions on stock markets?...
No experimentation. Lack of observation. No/ lack of/ full (?) mathematization.
Very hot issue; more papers, more projects, more money...
d1, d2, d3, ...p1, p2, p3, ...D={di}P={pj}f(D) = P
DataProblem d1 p1 d2 p2 d3 p3 d4 p4 ... ...calculation=thinking
About 100 data and/or questions per day.Relevancy and weights of dj pk connections.
f(dj)=pk
For a specific stock
kmax=1 and p1= for each investor i.
-1 i +1 and
-1 i Si 0 SELL 0 Bi i +1 BUY,
where Si and Bi are personal tresholds, both can be set to 0 as default.
i = i(t) decision is made at t.
If mi(t) is the portfolio value of the investor i
mi(t)=i(t) + i(t) i(t)=i(t) + i(t),
where is the liquid, stock amount and is initial capital, net gain.
mi(t)i(t) defines the whole market at t.
mi(t)i(t) mi(t-)i(t-) market is SOLD in mi(t)i(t) mi(t-)i(t-) market is BOUGHT
i(t)i(t) i(t-)i(t-) market is (expected) to be BOUGHT in the next i(t)i(t) i(t-)i(t-) market is (expected) to be SOLD
All the resulting information becomes new data djs (for the next ).
Time constants All investors aim is to make profit. Buy cheap sell expensive Investors profile is nonuniform, so is i(t). (Investors profile displays the same distrubution as in society.)
AssumptionsInvestors are close followers, aware of all information and news. (tight-binding approach )Investors are reflexive, decide and behave immediately. (pseudo-potential approach ) Then i(t) equals to tendencies and actions at the same time.
Mathematisation
All the resulting information on the previous slide become new dj (for the next time period ).
Iterative methods
Optimization of i(t)i(t)s,where stands for any of , , , and .
Any more?
TOASO 22.11.2004
-%0,66
INCLUDEPICTURE "http://www.bigpara.com/graph/20041122180640280.gif" \* MERGEFORMATINET
ADANA-C 22.11.2004
+%9,68
THYAO 22.11.2004
%0.0
COMUN 22.11.2004
-%9,09
BLEK 22.11.2004
%-1,06
TOASO 22.11.2004
%0,00
INCLUDEPICTURE "http://www.bigpara.com/graph/20041123173737280.gif" \* MERGEFORMATINET
ADANA-C 22.11.2004
+%2,94
THYAO 22.11.2004
%0.0
COMUN 22.11.2004
+%4,17
BLEK 22.11.2004
+%2,36
ENDEKS HSSELER
Hisse Kodu
irket Ad
HAO%
Piyasa Deg.(Milyon $)
Tahmini Arlk(%)
Kmlatif Arlk(%)
1
ISCTR
T. Bankas A..
33
7,739.4
12.9
12.9
2
AKBNK
Akbank T.A..
28
7,127.9
10.1
22.9
3
TCELL
Turkcell letiim Hizmetleri A..
14
9,016.8
6.4
29.3
4
EREGL
Ereli D elik Fabrikalar T.A..
49
2,028.5
5.0
34.3
5
GARAN
T. Garanti Bankas A..
32
2,935.0
4.7
39.0
6
TUPRS
Tpra Trkiye Petrol Rafinerileri A..
34
2,537.4
4.3
43.4
7
YKBNK
Yap ve Kredi Bankas A..
42
2,008.4
4.3
47.6
8
KCHOL
Ko Holding A..
19
4,332.3
4.1
51.8
9
SAHOL
Sabanc Holding
19
3,790.4
3.6
55.4
10
AEFES
Anadolu Efes Biraclk ve Malt San.
36
1,845.8
3.3
58.8
11
MIGRS
Migros Trk T.A..
49
890.1
2.2
61.0
12
DOHOL
Doan irketler Grubu Holding A..
34
1,274.3
2.2
63.1
13
ARCLK
Arelik A..
20
2,152.1
2.2
65.3
14
SISE
T.ie ve Cam Fabrikalar A..
39
994.4
2.0
67.3
15
VESTL
Vestel Elektronik Sanayi ve Ticaret A..
63
555.9
1.8
69.0
16
FROTO
Ford Otomotiv Sanayi A..
17
2,043.5
1.8
70.8
17
DYHOL
Doan Yayn Holding A..
30
1,153.4
1.7
72.5
18
HURGZ
Hrriyet Gazetecilik ve Matbaaclk A..
40
809.6
1.6
74.1
19
ENKAI
Enka inaat ve Sanayi A..
12
2,585.6
1.6
75.7
20
ULKER
lker Gda San. A..
26
834.0
1.1
76.8
21
FINBN
Finansbank A..
31
667.9
1.0
77.8
22
TOASO
Tofa Trk Otomobil Fabrikas A..
24
849.1
1.0
78.9
23
AYGAZ
Aygaz A..
42
476.3
1.0
79.9
24
AKGRT
Aksigorta A..
38
487.5
0.9
80.8
25
TRKCM
Trakya Cam Sanayii A..
31
591.7
0.9
81.7
26
IHLAS
hlas Holding
61
300.6
0.9
82.6
27
KIPA
Tesco Kipa Kitle Paz. Tic. ve Gda San.
99
174.1
0.9
83.5
28
KRDMD
Kardemir
99
160.2
0.8
84.3
29
DISBA
T. D Ticaret Bankas A..
35
412.0
0.7
85.0
30
TNSAS
Tansa Parakende Maazaclk Tic. A..
43
334.7
0.7
85.8
_1162912147.bin
_1162912194.bin
Growth types
Random (arithmetical) growth:A = A0 Astate economies
Forced arithmetical growth:minimized Amaximized+A
YKBNK
Geometrical growth
A / A = r (r, constant)A1= A0 + rA0= (1+r) A0A2= A1 + rA1= (1+r)2A0A3= A2 + rA2= (1+r)3A0...An-1An+1=An2population
An= (1+r)nA0
Chart1
1.511
2.2522
3.37533
5.062544
7.5937555
11.39062566
multiple
#REF!
#REF!
term
multiples
50%'s
Chart2
11
1.51.3
2.251.69
3.3752.197
5.06252.8561
7.593753.71293
11.3906254.826809
17.08593756.2748517
25.628906258.15730721
38.44335937510.604499373
57.665039062513.7858491849
86.497558593817.9216039404
129.746337890623.2980851225
194.619506835930.2875106592
291.929260253939.373763857
437.893890380951.1858930141
656.840835571366.5416609183
985.261253356986.5041591938
1477.8918800354112.455406952
2216.8378200531146.1920290375
term
multy
,5's & ,3's
Sheet1
term0.50.3
011
11.51.3
22.251.69
33.3752.197
45.06252.8561
57.593753.71293
611.3906254.826809
717.08593756.2748517
825.628906258.15730721
938.44335937510.604499373
1057.665039062513.7858491849
1186.497558593817.9216039404
12129.746337890623.2980851225
13194.619506835930.2875106592
14291.929260253939.373763857
15437.893890380951.1858930141
16656.840835571366.5416609183
17985.261253356986.5041591938
181477.8918800354112.455406952
192216.8378200531146.1920290375
Sheet1
term
1/2 & 1/3
Exponential growth
A/A = nr
An=enrinformation, bacteria, garbage
Q: Can we manage extreme (geometrical or exponential) growths of portfolios in stock market (IMKB)?...
A: Yes!...
FMIZP, ADANA-c, ECZYT, ... too expensive
Q: New & cheap ones?
A: Yes!
Summary: Hamsi fishing or whale hunting...
Yours questions please...
Thanks a lot for yours kindly interest and listenning...
a bis
ANHYT
_1163268009.bin