22 Google Trends Estimation of Stock Dealing Timing using Google Trends

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1 22 Google Trends Estimation of Stock Dealing Timing using Google Trends

2

3 Google Trends Google Trends Google Google Google Trends Google Trends 2006 Google Google Trend i

4

5 Abstract Estimation of Stock Dealing Timing using Google Trends OHIGASHI, Makoto Google Trends displays frequency of a keyword that is input to Google search engine by users in the world. We apply the data of Google Trends to the estimation of the timing of stock trading. The information retrieval frequency of the keyword is related to the attention to a company by the internet users. In general, property of a company and sales achievement are greatly related to the stock prices and the people s attention to the company or its product or service are also related to the company s stock price. The timing of fluctuation of stock price is able to be estimated more accurately by using the frequency data of retrieval by keyword by Google Trends in addition to the past stock price. We show that prediction result by proposed method using Google Trends is more accurate compared to conventional time series prediction. keywords Google, Google Trends, Frequency of keyword iii

6

7 Google Trends Google Trends v

8 A Google Trends Data 43 vi

9 ( ) (2006) (2006) (2006) (2006) f(t) g(t) f(t) g(t) ( A) ( B) ( C) ( D) ( E) A.1 A vii

10 A.2 B A.3 C A.4 D A.5 E A.6 F A.7 G A.8 H viii

11 ( A) ( B) ( C) ( D) ( E) ( F) ( G) H ix

12

13

14 PR(press release) PR 2

15 ( ) 1.4 3

16 ( )

17 1.2 = n n 100 (1.1) n

18 1 [3] [4] [5][6][7] 1.3 6

19 Google Trends

20

21 2 Google Trends 2.1 Google Trends 2.2 Google Trends Google Microsoft Google Google Trends Google Google Trends

22 2 Google Trends 2.1 (2006) Google web 10

23 2.3 Google Trends (2006)

24 2 Google Trends 2.3 (2006) 2.4 (2006) 4 7 Google Trends 12

25

26 n (x i1 x 1 )(x i2 x 2 ) (3.1) i 14

27 3.3 x i1 x i i (x i1 x 1 )(x i2 x 2 ) i (x i1 x 1 ) 2 i (x i2 x 2 ) 2 (3.2) x 1 x 1 (3.3) f, g 15

28 3 (f g)(m) = 1 n 1 f(i)g(i + m) (3.4) i 2 f(t), g(t) (f(t), g(t)) 3.2 f(t) 3.3 g(t) 16

29 f(t) g(t) 17

30

31 4 Google Trends

32 4 4.1 Google Trends 4.2 Google Trends Google Trends Google Trends

33 4.4 [ ( )] Google Trends Google Trends Google Trends

34 4 4.2 ( A) 4.3 ( B) 22

35 ( C) 4.5 ( D) 23

36 4 4.6 ( E)

37 4.4 A ( ) ( A) 70 25

38 4 B ( ) ( B) 70 26

39 4.4 C ( ) ( C) B 70 27

40 4 D ( ) ( D)

41 4.4 E ( ) ( E)

42 4 F ( ) ( F)

43 4.4 G ( ) ( G)

44 4 H ( ) H

45 5 Google Trends Google Trends 4 91% 61% 100% 20% 10 33

46 5 34

47 6 Google Trends Google Trends Google Trends 35

48 6 36

49

50 1 1 1! 3 38

51 50km

52

53 [1],Vol. 22, pp.1e2-04, 2004 [2], March., 1999 [3],376 pp March., 1998 [4] :, Vol. 126, No. 11, pp (2006). [5], June., 1992 [6], June., 2001 [7] :, Vol. 129, No. 7, pp (2009). [8],

54

55 A Google Trends Data A.1 A 4 A GoogleTrends 43

56 A Google Trends Data A.2 B 4 B GoogleTrends 44

57 A.3 C 4 C GoogleTrends 9 45

58 A Google Trends Data A.4 D 4 D GoogleTrends 46

59 A.5 E 4 E GoogleTrends 47

60 A Google Trends Data A.6 F 4 F GoogleTrends 2 48

61 A.7 G 4 G GoogleTrends 11 49

62 A Google Trends Data A.8 H 4 H GoogleTrends 3 50

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..,,,, , ( ) 3.,., 3.,., 500, 233.,, 3,,.,, i 25 Feature Selection for Prediction of Stock Price Time Series 1140357 2014 2 28 ..,,,,. 2013 1 1 12 31, ( ) 3.,., 3.,., 500, 233.,, 3,,.,, i Abstract Feature Selection for Prediction of Stock Price Time

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