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The impact of Gold, Bond, Currency, Metals and Oil markets on the USA stock market

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TLDR
In this paper, the authors examined the impact of financial and economic variables on the industrial Dow Jones Industrial Average (DJIA) using daily data over the sample period March 1995 - May 2014.
Abstract
This study examines the impact of financial and economic variables on the industrial Dow Jones Industrial Average (DJIA) using daily data over the sample period March 1995 - May 2014. Gold, Bond, Currency, Metals and Oil market were taken into consideration, and, as well as, their impact on the DJIA. The results of the model GJR – GARCH proved that the purchase of gold, of decade bonds (10 Year Treasury Note) and the U.S. Dollar/Yen exchange rate affect, negatively, the returns of DJIA.  On the other hand, it was made clear that the purchase of industrial metals affects, positively, the returns of DJIA. Lastly, our findings indicate that the asymmetry of the oil returns affects- extremely negatively- the DJIA returns. Keywords : GJR-GARCH, Brent oil, Gold, Metals, Equity market, Exchange rates, Bond market, market risk J EL Classifications: C5; G1; G32; R3

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Macroeconomic factors’ influence on “new” European countries stock returns: the case of four transition economies

TL;DR: In this paper, the authors investigated whether current and future domestic and international macroeconomic variables can explain long and short run stock returns in four “new” European countries (Poland, Czech Republic, Slovakia and Hungary).
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Relationship between Oil and Stock Markets: Evidence from Pakistan Stock Exchange

TL;DR: In this article, the impact of price variations in global markets, specifically oil, on stock returns at Pakistan Stock Exchange (PSX) has been studied for a period 2009-20 to provide evidence.
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An augmented macroeconomic linear factor model of South African industrial sector returns

TL;DR: In this article, the authors investigated the impact of the macroeconomic environment on South African industrial sector returns and found that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy.
References
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Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation

Robert F. Engle
- 01 Jul 1982 - 
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
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Generalized autoregressive conditional heteroskedasticity

TL;DR: In this paper, a natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in 1982 to allow for past conditional variances in the current conditional variance equation is proposed.
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Conditional heteroskedasticity in asset returns: a new approach

Daniel B. Nelson
- 01 Mar 1991 - 
TL;DR: In this article, an exponential ARCH model is proposed to study volatility changes and the risk premium on the CRSP Value-Weighted Market Index from 1962 to 1987, which is an improvement over the widely-used GARCH model.
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On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks

TL;DR: In this article, a modified GARCH-M model was used to find a negative relation between conditional expected monthly return and conditional variance of monthly return, using seasonal patterns in volatility and nominal interest rates to predict conditional variance.
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Measuring and Testing the Impact of News on Volatility

TL;DR: This paper defined the news impact curve which measures how new information is incorporated into volatility estimates and compared various ARCH models including a partially nonparametric one with daily Japanese stock return data.
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