Time Series Analysis and the Relationship Between Stock Prices and House Prices in Korea

AbstractSince macroeconomic fundamentals have been found to play a vital role for changes in the economy of a country. Consequently, the onus is on the appropriate regulatory authorities to take measures in making amendments in these policies to put the economy on the right development track. The aim of this study is to use time series analysis to empirically showcase the nexus between macroeconomic fundamentals and stock prices in Nigeria. The method used for this study was the Co-integration test and the EGARCH technique to estimate the possible influence of the selected macroeconomic fundamentals on stock prices. Volatility was captured by using quarterly data and estimated using GARCH (1,1) respectively. The study found there is a positive relationship between macroeconomic factors and stock prices in Nigeria. Therefore, the study recommends that the Federal authority should put in place policy measures that will enable the exchange rate to be relatively stabilized. This is because empirical evidence from studies has shown that exchange rate affects stock market prices. In addition, the government authority should ensure an enabling environment that would build the mindset of institutional investors in the Nigerian stock market due to the existence of information asymmetry problems among potential investors.

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Market Response, Competitive Behavior, and Time Series Analysis

Journal of Marketing Research ◽

10.1177/002224378001700406 ◽

1980 ◽

Vol 17 (4) ◽

pp. 470-485 ◽

Cited By ~ 40

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.

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From time series analysis to a modified ordinary differential equation

Journal of Algorithms & Computational Technology ◽

10.1177/1748301817751480 ◽

2018 ◽

Vol 12 (2) ◽

pp. 85-90

Author(s):

Meiyu Xue ◽

Choi-Hong Lai

Keyword(s):

Differential Equation ◽

Ordinary Differential Equation ◽

Time Series ◽

Time Series Analysis ◽

Stock Prices ◽

Time Frame ◽

Equation Approach ◽

Advantages And Disadvantages ◽

Series Analysis ◽

Bank Stock

In understanding Big Data, people are interested to obtain the trend and dynamics of a given set of temporal data, which in turn can be used to predict possible futures. This paper examines a time series analysis method and an ordinary differential equation approach in modeling the price movements of petroleum price and of three different bank stock prices over a time frame of three years. Computational tests consist of a range of data fitting models in order to understand the advantages and disadvantages of these two approaches. A modified ordinary differential equation model, with different forms of polynomials and periodic functions, is proposed. Numerical tests demonstrated the advantage of the modified ordinary differential equation approach. Computational properties of the modified ordinary differential equation are studied.

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

Communist and Post-Communist Studies ◽

10.1016/j.postcomstud.2014.01.008 ◽

2014 ◽

Vol 47 (1) ◽

pp. 93-103 ◽

Cited By ~ 2

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.

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