Big Data Time Series Analysis of the Relationship Between News Coverage, Apartment Price and Trading Volume

2020 ◽  
Vol 24 (2) ◽  
pp. 53-69
Author(s):  
Hae-Jung Chun
Keyword(s):  
Time Series ◽  
Big Data ◽  
Time Series Analysis ◽  
Trading Volume ◽  
News Coverage ◽  
Series Analysis ◽  
The Relationship

A NEW APPROACH OF BIVARIATE FUZZY TIME SERIES ANALYSIS TO THE FORECASTING OF A STOCK INDEX

2003 ◽  
Vol 11 (06) ◽  
pp. 671-690 ◽  
Author(s):  
YU-YUN HSU ◽  
SZE-MAN TSE ◽  
BERLIN WU
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Trading Volume ◽  
Arma Model ◽  
Future Trend ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
New Approach ◽  
Series Analysis ◽  
Closing Price

In recent years, the innovation and improvement of forecasting techniques have caught more and more attention. Especially, in the fields of financial economics, management planning and control, forecasting provides indispensable information in decision-making process. If we merely use the time series with the closing price array to build a forecasting model, a question that arises is: Can the model exhibit the real case honestly? Since, the daily closing price of a stock index is uncertain and indistinct. A decision for biased future trend may result in the danger of huge lost. Moreover, there are many factors that influence daily closing price, such as trading volume and exchange rate, and so on. In this research, we propose a new approach for a bivariate fuzzy time series analysis and forecasting through fuzzy relation equations. An empirical study on closing price and trading volume of a bivariate fuzzy time series model for Taiwan Weighted Stock Index is constructed. The performance of linguistic forecasting and the comparison with the bivariate ARMA model are also illustrated.

scholarly journals Market Response, Competitive Behavior, and Time Series Analysis

1980 ◽  
Vol 17 (4) ◽  
pp. 470-485 ◽  
Author(s):  
Dominique M. Hanssens
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Model Building ◽  
Competitive Reaction ◽  
Marketing Model ◽  
Series Analysis ◽  
Marketing Variables ◽  
Major Airlines ◽  
Market Variables ◽  
The Relationship

The author's principal objective is to present a framework for market analysis which specifically models primary demand, competitive reaction, and feedback effects of the market variables. The approach is an extension of earlier work by Clarke and by Lambin, Naert, and Bultez on the relationship among the elasticities of the marketing variables. The author develops this framework and formulates an approach for empirical applications based on principles of time series analysis. In particular, Granger's well-known causality definition is used in conjunction with Box-Jenkins analysis to find the nonzero elements in the marketing model. These principles are applied empirically to the case of a city pair of the U.S. domestic air travel market, where three major airlines compete on the basis of flight scheduling and advertising. The analysis reveals that flight scheduling has a market-expansive or a competitive effect, depending on the competitor, and that advertising does not have a significant impact on performance. In addition, several patterns of competitive reactions are found. The author offers observations on the theoretical and empirical aspects of this approach to marketing model building.

Television and protest in East Germany’s revolution, 1989–1990: A mixed-methods analysis

2014 ◽  
Vol 47 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Marko Grdešić
Keyword(s):  
Time Series ◽  
Mixed Methods ◽  
Time Series Analysis ◽  
Qualitative Analysis ◽  
Event Data ◽  
Mixed Methods Approach ◽  
Series Analysis ◽  
East German ◽  
Television Coverage ◽  
The Relationship

This article uses a mixed-methods approach to analyze the relationship between television and protest during East Germany’s revolution. The content of television newscasts, both West German and East German, is analyzed together with protest event data. There are two key findings. First, West German coverage of protests is associated with an increase in protest in the first phase of the revolution. This finding emerges from time series analysis. Second, West German and East German television coverage were interacting, with the latter reacting to the former. This finding emerges from both quantitative and qualitative analysis.

scholarly journals Time-series analysis of abundance indices of young fish

2004 ◽  
Vol 61 (2) ◽  
pp. 176-183 ◽  
Author(s):  
G. Gudmundsson
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Large Deviation ◽  
Natural Mortality ◽  
Cohort Size ◽  
Young Fish ◽  
Stock Size ◽  
Series Analysis ◽  
Abundance Indices ◽  
The Relationship

Abstract Catch-at-age analysis provides estimates of stock size at ages when the fish have reached catchable size. Survey indices contain information about relative cohort size at younger ages. The present analysis is concerned with survey indices of juveniles up to the youngest age where stock estimates, based on time-series analysis of catch-at-age data, are available. A stock estimate at that age from catch-at-age data is also included. A common model of the relationship between stock size and survey indices is combined with the model describing the decline of a stock by natural mortality. Random variations in natural mortality are defined separately from sampling variations and irregular catchability in the survey. The stock size and magnitudes of the random variations are estimated by the Kalman filter, which also provides predictions of future recruitment to the catchable stock. Analysis of observations of Icelandic cod reveals a large deviation from proportionality in the relationship between the index and the stock estimates in the youngest ages, but haddock data are compatible with proportionality. Variations in natural mortality during the second to fourth year of cod and the second to third year of haddock are not a major factor in variations of stock size.

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