An Empirical Analysis of the Relationship between Oil Prices and Stock Markets

Markoulis, Stelios; Neofytou, Niki

doi:10.5539/ijef.v8n12p120

Cited by 8 publications

(7 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current article is relevant to some other articles that investigate corporate share-holding under the prism of the SEO/TTF timing. In this frame, some articles (Choie, 2016;Markoulis & Neofytou, 2016) targeted on the information asset and stock-taking intelligence of corporate investors, while others (Hao, 2014;Baker, Stein, & Wurgler, 2003) targeted the trading strategies and plans, but in both cases no TTF information was given. Gibson, Safieddine, and Sonti (2004) report that seasoned equity and option SEO initiatives, with the bigger boost in corporate share-holding, are detected between the (relative to SEO/TTF, SEO timing) quarters −1 and +1; these long-term investors reported that their positions outperform in the subsequent the SEO issue year and qualify this outperform to their competitive convenience asset position.…”

Section: Relevant Scholarship Descriptionmentioning

confidence: 99%

Seasoned Equity Offerings as Technical Market Anomalies: Long-Term Temporal Trading Functionalities

Basdekidou¹

2016

IJEF

View full text Add to dashboard Cite

<p>The main goal of this paper is to approach the Seasoned Equity Offerings (SEO) trading opportunities as technical market anomalies and under the prism of a number of temporal (time-based) long-term trading functionalities (long-term TTF) introduced for the first time in corporate finance literature. The long-term is defined, for the purposes of this paper, as the 3-year time period, traded usually with daily, weekly and monthly time-frames. Trading is a temporal (i.e. time-based) historical living system with a number of functions, like: SEO, IPO, stock (instrument) price action Gaps, Breakouts, etc. In this domain, a number of warning long-term and short-term dynamics timing functionalities is available, like: candlestick patterns breaks, price action patterns pivotal-lines breaks, on open gup-ups (ooGUp), on open gup-downs (ooGDn), morning breakouts (mB), etc. All these time-based functionalities are regarded as 2<sup>nd</sup> level functions (i.e. functions of functions; because of the timing involved) with great trading opportunities, and they are defined –for the first time in the corporate finance literature- by this paper as temporal (timing) trading functionalities. In particular, the SEOs with the embedded long-term TTF functionalities are great trading opportunities for the institutions, the individual (non-commercial) market investors, the swing traders, and the speculators. Data analysis shows that during the seasoned equity offerings time, shareowners significantly increase their share-holding, including offerings that would be classified as overpriced at that time; hence, the involved trading volatility is increased resulting in great trading and profit opportunities. This paper contributes to corporate finance literature by examining the SEOs functions and define and document their inherit TTF functionalities. For this purpose, four categories of share-holders are regarded: The long-term institution & non-commercial traders (investors), the swing momentary institution traders (institutions), the short-term non-commercial traders (speculators) and the intraday non-commercial traders (speculators). Paper concludes that, in SEO/long-term TTF trading, apart from the insiders, the swing traders (usually the smart-money and the institutions) are more benefited, at the expense of momentary short-term and intraday speculators, while the long-term investors are not affected by the SEO offerings.</p>

show abstract

Section: Relevant Scholarship Descriptionmentioning

confidence: 99%

Seasoned Equity Offerings as Technical Market Anomalies: Long-Term Temporal Trading Functionalities

Basdekidou¹

2016

IJEF

View full text Add to dashboard Cite

show abstract

“…Similarly, other surveys show that oil shocks do not influence stock market returns in either a positive or negative way. Another study indicated that oil price has no long-term impact in the G7 countries as it does in emerging economies like Brazil, Russia, India, and China (BRIC) states (Markoulis & Neofytou, 2016). The unrelated results can be explained by the different degree of dependence on oil in various economies.…”

Section: Introductionmentioning

confidence: 99%

“…Statistics indicate the high interdependence rates between crude oil prices and the stock market returns in the 1990s (Markoulis & Neofytou, 2016). This correlation is associated with the influx in the housing market which influenced the Organization of the Petroleum Exporting Countries (OPEC) to stimulate oil production.…”

Section: Introductionmentioning

confidence: 99%

Symmetric and Asymmetric GARCH Estimations and Portfolio Optimization: Evidence From G7 Stock Markets

et al. 2019

View full text Add to dashboard Cite

Volatility exchanges between equity markets and oil markets are vital for portfolio designing and risk management. This study empirically analyses the interdependence of stock and oil market for G7 countries. For econometric estimations, we used the data of G7 countries' stock markets for the period of 2000-2016. Dynamic conditional correlation and corrected dynamic conditional correlation are employed for symmetric estimation. We find differences in the magnitudes of negative and positive oil price shocks of G7 countries. The study also uses the asymmetric estimations to examine the response of different shocks, and the variance and covariance series of these estimations are used for portfolio optimization and hedging of stock and oil assets. The findings of symmetric and asymmetric estimations depict that past news and lagged volatility have a significant impact on the current conditional volatility of G7 stock markets. On the contrary, the current conditional volatility in the oil market is less dependent on past news and lagged volatility in the oil market. Our results portray that G7 stock markets are more sensitive to past news and lagged volatility than oil markets. FIGARCH and FIEGARCH provide evidence of an intermediate range of persistence of volatility. Finally, portfolio estimations report the importance of oil assets to form an optimal portfolio that can minimize the portfolio risk without changing the expected return. Based on our findings, we suggest that investors and portfolio managers of G7 countries should formulate a portfolio of stock and oil assets to manage their portfolio risk.

show abstract

“…In this frame, some articles (Choie, 2016;Markoulis & Neofytou, 2016) targeted on the information asset and stock-taking intelligence of corporate investors, while others (Hao, 2014;Baker, Stein, & Wurgler, 2003;Gibson, Safieddine, & Sonti, 2004) targeted on the trading strategies, tactics and plans, but in both cases no TTF information was given.…”

Section: Motivation and Previous Literaturementioning

confidence: 99%

The Overnight Return Temporal Market Anomaly

Basdekidou

2017

IJEF

View full text Add to dashboard Cite

The main goal of this paper is to introduce an innovative market anomaly relating to "time" during the overnight post-market session and therefore characterized as a temporal market anomaly. Anomalies in the markets appear from time to time and test the efficient market hypothesis. Many investors and traders believe that the markets follow the efficient market hypothesis. According to this theory the current price of a security (trading instrument) reflects all public and private information about that security (instrument). Changes in price are due to insider information, current news, or sudden events, which are impossible to predict. Hence, security's price action follows the path of a random walk, the hypothesis and argument of which states that current price is not dependent on past price and is normally or abnormally distributed over time. In financial and economical literature, many studies have presented approaches about what the academics call "market anomalies" and according to literature the anomalies are classified in three categories: Fundamental, Technical, and Calendar-based anomalies. In this article another class of market anomalies is introduced, that simply could be referred to as "temporal" because of the timing functionality involved. Finally, I will discuss one of these "temporal" anomalies, called the overnight return temporal market anomaly. The presented research shows that momentum profit accumulates entirely overnight, while profit on all other strategies occurs entirely intraday. These findings strongly reject classical theories of intraday versus overnight returns.

show abstract

An Empirical Analysis of the Relationship between Oil Prices and Stock Markets

Cited by 8 publications

References 50 publications

Seasoned Equity Offerings as Technical Market Anomalies: Long-Term Temporal Trading Functionalities

Seasoned Equity Offerings as Technical Market Anomalies: Long-Term Temporal Trading Functionalities

Symmetric and Asymmetric GARCH Estimations and Portfolio Optimization: Evidence From G7 Stock Markets

The Overnight Return Temporal Market Anomaly

Contact Info

Product

Resources

About