Does oil price volatility matter for Asian emerging economies?

This article investigates the impact of oil price volatility on six major emerging economies in Asia using time-series cross-section and time-series econometric techniques. To assess the robustness of the findings, we further implement such heterogeneous panel data estimation methods as Mean Group (MG), Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators to allow for cross-sectional dependence. The empirical results reveal that oil price volatility has a detrimental effect on these emerging economies. In the short run, oil price volatility influenced output growth in China and affected both GDP growth and inflation in India. In the Philippines, oil price volatility impacted on inflation, but in Indonesia, it impacted on both GDP growth and inflation before and after the Asian financial crisis. In Malaysia, oil price volatility impacted on GDP growth, although there is notably little feedback from the opposite side. For Thailand, oil price volatility influenced output growth prior to the Asian financial crisis, but the impact disappeared after the crisis. It appears that oil subsidization by the Thai Government via introduction of the oil fund played a significant role in improving the economic performance by lessening the adverse effects of oil price volatility on macroeconomic indicators.

Has oil price predicted stock returns for over a century?

This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150. years (1859:10-2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroscedasticity. Three key findings are unraveled: first, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.

Oil price and stock returns of consumers and producers of crude oil

In this paper we investigate how differently stock returns of oil producers and oil consumers are affected from oil price changes. We find that stock returns of oil producers are affected positively by oil price changes regardless of whether oil price is increasing or decreasing. For oil consumers, oil price changes do not affect all consumer sub-sectors and where it does, this effect is heterogeneous. We find that oil price returns have an asymmetric effect on stock returns for most sub-sectors. We devise simple trading strategies and find that while both consumers and producers of oil can make statistically significant profits, investors in oil producer sectors make relatively more profits than investors in oil consumer sectors.

Psychological oil price barrier and firm returns

In this paper, we investigate the psychological barrier effect induced by the oil price on firm returns when the oil price reaches US$100 or more per barrel. We find evidence of the negative effect of the US$100 oil price barrier for: (a) the entire sample of 1559 firms listed on the American stock exchanges; (b) both foreign and domestic firms, with domestic firms significantly more affected; (c) the 10 different sizes of firms, with the smaller firms less affected compared to the larger firms; and (d) 17 sectors of firms, with firms in the utilities, mining, and administration sectors being the least affected.

Oil price shocks and policy implications the emergence of U.S. tight oil production: a case study

How have shocks to supply and demand affected global oil prices; and what are key policy implications following the resurgence of oil production in the United States? Highlights: − The recent collapse in global oil prices was dominated by oversupply. − The future of tight oil in the United States is vulnerable to obstacles beyond oil prices. − Opinions on tight oil from the Top 25 think tank organizations are considered. Global oil prices have fallen more than fifty percent since mid-2014. While price corrections in the global oil markets resulted from multiple factors over the past twelve months, surging tight oil production from the United States was a key driver. Tight oil is considered an unconventional or transitional oil source due to its location in oil-bearing shale instead of conventional oil reservoirs. These qualities make tight oil production fundamentally different from regular crude, posing unique challenges. This case study examines these challenges and explores how shocks to supply and demand affect global oil prices while identifying important policy considerations. Analysis of existing evidence is supported by expert opinions from more than one hundred scholars from top-tier think tank organizations. Finally, implications for United States tight oil production as well as global ramifications of a new low price environment are explored.

Some further empirical evidence on the impact of oil price changes on petrol prices

This paper analyses the asymmetries in the response of petrol prices to oil price shocks. We show that previous work, based on the determination of asymmetric responses, can be improved upon by allowing for asymmetries in short term dynamics. The paper shows that a significant determinant of the response of petrol prices to oil price changes, is the extent to which petrol price can be seen to have departed from its long run equilibrium level.

Az olajár gyengülő makrogazdasági hatásai. Két versengő elmélet szintézise = Weakening macroeconomic effects of the oil price. A synthesis of two competing theories

Az 1970-es évek olajválságait követő stagflációs periódusok óta gyakorlatilag minden nagyobb áremelkedés alkalmával felerősödnek a kedvezőtlen makrogazdasági hatásokkal kapcsolatos félelmek, miközben a tapasztalat azt mutatja, hogy az importőröket egyre kevésbé érinti az olaj reálárának alakulása. A gyengülő hatások okaként Blanchard-Galí [2007] a gazdaságok hatékonyabb és rugalmasabb működését jelölte meg, míg Kilian [2010] szerint a 2000 utáni áremelkedést a kedvező világgazdasági környezet fűtötte, ami ellensúlyozta a magasabb ár okozta negatív folyamatokat. A tanulmány Kilian [2009] modelljének kiterjesztésével, időben változó paraméterű ökonometriai eljárással vizsgálja a két megközelítés összeegyeztethetőségét. Az eredmények a hipotézisek egymást kiegészítő kapcsolatára engednek következtetni, azaz a makrogazdasági következmények szempontjából nem maga az ár, hanem annak kiváltó okai lényegesek, ugyanakkor e mögöttes tényezők hatása az elmúlt évtizedekben folyamatosan változott. _____ Many economists argue that the stagflation periods of the 1970s were related to the two main oil crises. However, experience shows that these effects were eliminated over the decades, e. g. oil-importing economies enjoyed solid growth and low inflation when oil prices surged in the 2000s. Blanchard and Galí (2007) found that economies became more effective and elastic in handling high energy prices, while Kilian (2010) took as the main reason for the weakening macroeconomic effects of oil-price shocks the structural differences behind the price changes. The article sets out to test the compatibility of the two rival theories, using time-varying parameter models. The results show that both hypotheses can be correct concurrently: the structure of the change in price matters, but the impulse responses varied over time.

Forecasting the term structure of volatility of crude oil price changes

Peer reviewed

Elderly demonstrate against oil price hike

General note: Title and date provided by Bettye Lane.

Oil Price Trackers Inspired by Immune Memory

We outline initial concepts for an immune inspired algorithm to evaluate and predict oil price time series data. The proposed solution evolves a short term pool of trackers dynamically, with each member attempting to map trends and anticipate future price movements. Successful trackers feed into a long term memory pool that can generalise across repeating trend patterns. The resulting sequence of trackers, ordered in time, can be used as a forecasting tool. Examination of the pool of evolving trackers also provides valuable insight into the properties of the crude oil market.

What drives the commodity price beta of oil industry stocks

We test theoretical drivers of the oil price beta of oil industry stocks. The strongest statistical and economic support comes for market conditions-type variables as the prime drivers: namely, oil price (+), bond rate (+), volatility of oil returns (−) and cost of carry (+). Though statistically significant, exogenous firm characteristics and oil firms' financing decisions have less compelling economic significance. There is weaker support for the prediction that financial risk management reduces the exposure of oil stocks to crude oil price variation. Finally, extended modelling shows that mean reversion in oil prices also helps explain cross-sectional variation in the oil beta.

Does the price of oil interact with clean energy prices in the stock market?

In this paper, we analyze the relationships among oil prices, clean energy stock prices, and technology stock prices, endogenously controlling for structural changes in the market. To this end, we apply Markov-switching vector autoregressive models to the economic system consisting of oil prices, clean energy and technology stock prices, and interest rates. The results indicate that there was a structural change in late 2007, a period in which there was a significant increase in the price of oil. In contrast to the previous studies, we find a positive relationship between oil prices and clean energy prices after structural breaks. There also appears to be a similarity in terms of the market response to both clean energy stock prices and technology stock prices. © 2013 Elsevier B.V.

Stock prices of clean energy firms, oil and carbon markets : a vector autoregressive analysis

Recent discussions of energy security and climate change have attracted significant attention to clean energy. We hypothesize that rising prices of conventional energy and/or placement of a price on carbon emissions would encourage investments in clean energy firms. The data from three clean energy indices show that oil prices and technology stock prices separately affect the stock prices of clean energy firms. However, the data fail to demonstrate a significant relationship between carbon prices and the stock prices of the firms.