Dynamic relationships between industry returns and stock market returns

Chen, Mei‐Ping; Chang, Chi-Hung

doi:10.1016/j.najef.2013.08.002

Cited by 25 publications

(13 citation statements)

References 68 publications

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“…6 In other words, dividends are reinvested. As standard in the literature, all returns are measured in US dollars (Bilson et al, 2001;Chambet & Gibson, 2008;de Jong & de Roon, 2005;Donadelli, 2013;Donadelli & Persha, 2013;Donadelli & Prosperi, 2012;Grootveld & Salomons, 2003;Lee, Chen, & Chang, 2013;Pukthuanthong & Roll, 2009). Note that returns denominated in US dollars retain only US inflation, are consistent with US macroeconomic variables' currency, and are homogeneous across Asian economies.…”

Section: A Brief Review Of the Literaturementioning

confidence: 99%

Asian stock markets, US economic policy uncertainty and US macro-shocks

Donadelli

2014

New Zealand Economic Papers

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Section: A Brief Review Of the Literaturementioning

confidence: 99%

Asian stock markets, US economic policy uncertainty and US macro-shocks

Donadelli

2014

New Zealand Economic Papers

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“…In other words, Chien-Chiang Lee et al (2013) found a bi-directional dynamical causal relationship between the industry returns and stock market returns. They also stated that the consumer service industry returns have a significant power in explaining the movements of the market returns.…”

Section: Relationship Between Interest Rate and Stock Return Of Nonfimentioning

confidence: 99%

“…Actually, as it includes Europe, USA, and China and provides evidence for two different nonfinancial sectors (industry and technological sector). Most other studies focus on nonfinancial sector or type of risk a single of country (see Prabhath and Tsui 2008;Lee et al 2013) which allow for both types of risk mainly the studies of the Japanese and the industrial sectors (see Prabhath and Tsui 2008). Second, we carry out our extensive analysis using an appropriate econometric methodology (a four-variate GARCH-M framework) which enables us to jointly model the nonfinancial sector, the stock market, the interest rate, and the exchange rate risk by estimating their conditional volatilities.…”

Section: Introductionmentioning

confidence: 99%

Stock Market, Interest Rate and Exchange Rate Risk Effects on non Financial Stock Returns During the Financial Crisis

Aloui

Jarboui

2015

J Knowl Econ

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In this paper, we examine the sensitivity of nonfinancial sector stock returns to the market, exchange rate risk, and interest rates in two nonfinancial sectors (technology and industry) in eight countries, including various European economies, the USA and China, over the period 2006-2009. We also test for the presence of causality-in-mean and volatility spillovers. The empirical results show that the stock market returns, interest rate, and exchange rate in most cases have a significant effect (positive and negative) during crisis. As for the three types of risk, these are found to play a role mainly in the industry sector. These empirical insights are in most cases of volatility spillovers occurring from market return to sectoral returns in the industry sector in European economies, though there are also some instances of the interest rate and exchange rate spillovers, both in Europe and in the USA, during the crisis.

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“…This approach [14] focuses on the industry leading affect by evaluating the industry, market, feedback and neutrality of a certain domain. Here is concluded that the stock market evolution can be predicted by looking at GDP growth rate, exports, oil price, the exchange rate, the interest rate, and government support.…”

Section: A Related Workmentioning

confidence: 99%

Intelligent Stock Market Analysis System - A Fundamental and Macro-economical Analysis Approach

Tirea

Negru

2014

2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

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Stock Market Forecasting implies the use of a series of techniques that helps in determining the stock price evolution. Stock Market Forecasting implies the use of a series of techniques that helps in determining the stock price evolution. The paper describes a multi-agent system that uses numerical, financial and economical data in order to evaluate the companys position on the market, profitability, performance, future expectations in the companys evolution. Determining the effect of political, governmental and social decisions along with detecting the way in which the price is constructed based on technical and fundamental analysis methods and the bid/ask situation helps in determining a more precise buy/sell signals, reducing the false signals and determining some risk/gain positions on different periods of time. In order to validate the results a prototype was developed.

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Dynamic relationships between industry returns and stock market returns

Cited by 25 publications

References 68 publications

Asian stock markets, US economic policy uncertainty and US macro-shocks

Asian stock markets, US economic policy uncertainty and US macro-shocks

Stock Market, Interest Rate and Exchange Rate Risk Effects on non Financial Stock Returns During the Financial Crisis

Intelligent Stock Market Analysis System - A Fundamental and Macro-economical Analysis Approach

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