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Can you really predict markets with ...

ProQuest Information and Learning Co.

Can you really predict markets with Twitter?

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Can you really predict markets with Twitter?/
Author:	Plenzick, Christopher.
Description:	1 online resource (48 pages)
Notes:	Source: Masters Abstracts International, Volume: 56-02.
Subject:	Economics. -
Online resource:	click for full text (PQDT)
ISBN:	9781369547511

Can you really predict markets with Twitter?
Plenzick, Christopher.

Can you really predict markets with Twitter? - 1 online resource (48 pages)

Source: Masters Abstracts International, Volume: 56-02.

Thesis (M.S.)--The University of North Dakota, 2016.

Includes bibliographical references

In this paper, I attempt to apply an emotional proxy derived by applying the Affective Norms for English Words (ANEW) to messages posted to the Twitter social networking service in order to forecast the movement two stock market indices: the Dow Jones Industrial Average (DJIA) and the CBOE Volatility Index (VIX). In contrast to previous works, I have compared the results of various forecast models employing different sentiment variables, as well as comparing the neural network approach to more standard logistic regression. Additionally, several of the models used employ an as-yet unique sentiment proxy, focusing on the average of expressed emotion rather than the volume of expressed emotion. The results indicate that while there is a distinct possibility that sentiment variables can assist in accurately forecasting market movement, the differences in choice of sentiment proxy and forecast method are less important than anticipated.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369547511Subjects--Topical Terms:

555568
Economics.
Index Terms--Genre/Form:

554714
Electronic books.

Can you really predict markets with Twitter?
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100 1 $a Plenzick, Christopher. $3 1185327
245 1 0 $a Can you really predict markets with Twitter?
264 0 $c 2016
300 $a 1 online resource (48 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-02.
500 $a Adviser: Xiao Wang.
502 $a Thesis (M.S.)--The University of North Dakota, 2016.
504 $a Includes bibliographical references
520 $a In this paper, I attempt to apply an emotional proxy derived by applying the Affective Norms for English Words (ANEW) to messages posted to the Twitter social networking service in order to forecast the movement two stock market indices: the Dow Jones Industrial Average (DJIA) and the CBOE Volatility Index (VIX). In contrast to previous works, I have compared the results of various forecast models employing different sentiment variables, as well as comparing the neural network approach to more standard logistic regression. Additionally, several of the models used employ an as-yet unique sentiment proxy, focusing on the average of expressed emotion rather than the volume of expressed emotion. The results indicate that while there is a distinct possibility that sentiment variables can assist in accurately forecasting market movement, the differences in choice of sentiment proxy and forecast method are less important than anticipated.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Economics. $3 555568
650 4 $a Finance. $3 559073
655 7 $a Electronic books. $2 local $3 554714
690 $a 0501
690 $a 0508
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of North Dakota. $b Applied Economics. $3 1185328
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10249387 $z click for full text (PQDT)

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