Oil prices and accounting profits of oil and gas companies

This paper investigates the relationship between commodity prices of crude oil, capital structure, firm size and accounting measures of firm performance using a sample of oil and gas firms from 1990 to 2008. We employ estimates based on panel least squares, a fixed effects model and a random effects model. We also use generalized method of moments (GMM) estimators by Arellano and Bond (1991) and Blundell and Bond (1998, 2000). Our findings show that crude oil prices positively and significantly impact the performance of oil and gas firms in North America using accounting measures of performance. The recent financial crisis of 2007 and 2008 negatively influenced oil prices and the financial performance of oil and gas firms. On the other hand, the earlier global crises (Asian financial crisis and 9/11) did not have a significant impact on the return on equity of oil and gas companies. Our primary contribution to the literature is a comprehensive and econometric analysis of the relation between commodity prices and accounting measures of performance oil and gas companies.     

Forecasting oil price realized volatility using information channels from other asset classes

Motivated from Ross (1989) who maintains that asset volatilities are synonymous to the information flow, we claim that cross-market volatility transmission effects are synonymous to cross-market information flows or “information channels” from one market to another. Based on this assertion we assess whether cross-market volatility flows contain important information that can improve the accuracy of oil price realized volatility forecasting. We concentrate on realized volatilities derived from the intra-day prices of the Brent crude oil and four different asset classes (Stocks, Forex, Commodities and Macro), which represent the different “information channels” by which oil price volatility is impacted from. We employ a HAR framework and estimate forecasts for 1-day to 66-days ahead. Our findings provide strong evidence that the use of the different “information channels” enhances the predictive accuracy of oil price realized volatility at all forecasting horizons. Numerous forecasting evaluation tests and alternative model specifications confirm the robustness of our results.     

Forecasting value‐at‐risk in oil prices in the presence of volatility shifts

Recent evidence suggests shifts (structural breaks) in the volatility of returns causes non‐normality by significantly increasing kurtosis. In this paper, we endogenously detect significant shifts in the volatility of oil prices and incorporate this information to estimate Value‐at‐Risk (VaR) to accurately forecast large declines in oil prices. Our out‐of‐sample performance results indicate that the model, which incorporates both time varying volatility (without making any distributional assumptions) and shifts in volatility, produces more accurate VaR forecasts than several benchmark methods. We make a timely contribution as the recent more frequent occurrences of unexpected large oil price declines has gained significant attention because of its substantial impact on the financial markets and the global economy.     

Basis variations and regime shifts in the oil futures market

The conditional volatility of crude oil futures returns is modelled as a regime switching process. The model features transition probabilities that are functions of the basis. Consistent with the theory of storage, in volatile periods, an increase in backwardation is associated with an increase in the likellihood of switching to or remaining in the high-volatility state. Conditional on regimes, GARCH persistence is significantly reduced. Out-of-sample tests show that incorporating regime shifts improves the accuracy of short-term volatility forecasts.     

Extreme events: a study of small oil and gas firms

The oil and gas industry is subject to different types of risks, many of which have the potential to generate extreme results. Classifying extreme events as global, industry specific and firm specific, we use a Bayesian probability model and the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model to evaluate the impact of disclosure of extreme events on returns and return volatilities. The results suggest political events have more of a pronounced effect compared to those classified as economic events. The overall effects are more pronounced at the global and firm‐level classifications. At the firm level, extreme economic events have a more significant impact than political extreme events.     

Heterogeneous expectations and long-range correlation of the volatility of asset returns

Inspired by the recent literature on aggregation theory, we attempt to relate the long-range correlation of the stock return volatility to the heterogeneity of the investors' expectations concerning the level of the future volatility. Based on a semi-parametric model of investors' anticipations, we make the connection between the distributional properties of the heterogeneity parameters and the auto-covariance/auto-correlation functions of the realized volatility. We report different behaviors, or change of convention, the observation of which depends on the market phase under consideration. In particular, we report and justify the fact that the volatility exhibits significantly longer memory during phases of a speculative bubble than during the recovery phase following the collapse of a speculative bubble.     

Industry upheaval and valuation: Empirical evidence from the international oil and gas industry

Accounting literature suggests that contemporaneous earnings are more useful than current operating cash flow in predicting future cash flows and, therefore, also more relevant for company valuation. However, recent research indicates that elevated levels of merger and acquisition activity or a changing economic environment may reduce the value relevance of earnings. Using the oil and gas industry as a case, this paper examines how the oil industry upheaval in the late 1990s influenced the value relevance of financial statement information. We extend the literature by testing for a structural shift in the equity market valuation process. Our results provide evidence of a structural break in the value relevance of accounting information. In contrast to prior research, we find that the value relevance of cash flows actually decreased in the recent oil industry upheaval. On the other hand, the value relevance of book equity increased. Furthermore, we find that accounting-method choice (full cost versus successful efforts) affects the value relevance of accounting information.     

The impact of monetary policy surprises on asset return volatility: the case of Germany

This paper investigates the impact of monetary policy surprises by the FED or Bundesbank/ECB on the return volatility of German stocks and bonds using a GARCH-M model. We show that stock return volatility is susceptible to monetary policy surprises in the United States, whereas monetary policy surprises in the Euro zone matter for bond return volatility. These findings are robust for other Euro zone stock markets, but not significant for other Euro zone bond markets. The empirical evidence also suggests that monetary policy surprises have larger effects on German stock return volatility in bear markets than in bull phases. Moreover, our results support the claim that stock return volatility can be negatively correlated with stock returns, contradicting predictions made by many asset pricing models (e.g., CAPM or ICAPM) and the empirical finding of an insignificant relationship often reported in the literature.

Information,interest rates,and the volatility of asset prices

The volatility of an asset price is modelled as a function of the volatility of an information signal, real interest rates and inflation expectations. Volatility depends on the duration of cash flows, and the degree to which cash flows are indexed to real rates and inflation. The model is applied to determine asset betas, the volatility of the futures prices of assets and the volatility of equity prices.     

Risk Transmission from Oil and Natural Gas Futures to Emerging Market Mutual Funds

This study evaluates the impacts of energy markets on emerging market mutual funds (EMMFs). In particular, we investigate the volatility transmission between these funds and the oil and natural gas prices. The findings suggest significant risk spillover from the energy markets to EMMFs. Furthermore, we find a large number of EMMFs’ risk transmitting to oil prices and almost all of the EMMFs’ risk transmitting to natural gas prices. By dividing the sample into two (before and after 2008), we find the EMMFs’ influence on the oil market decreasing after this turbulent period. Our results have important implications for mutual fund managers and investors.     

The determinants of the volatility of returns on cross-border asset holdings

Using both panel and cross-sectional models for 28 industrialized countries observed from 2001–2009, we report a number of findings regarding the determinants of the volatility of returns on cross-border asset holdings (i.e., equity and debt). Greater portfolio concentration and an increase in assets held in emerging markets lead to an elevation in earning volatility, whereas more financial integration and a greater share held in Organization for Economic Cooperation and Development countries and by the household sector cause a reduction in the return volatility. Larger asset holdings by offshore financial corporations and non-bank financial institutions cause higher market volatility, although they affect volatility in the equity and bond markets in the opposite way. Overall, both panel and cross-sectional estimations provide very similar results (albeit of different magnitude) and are robust to the endogeneity problem.     

Future Stock Performance of Oil and Gas Firms Conditional on the Imputed Value of Reserves

Review of Quantitative Finance and Accounting - Harris and Ohlson (1990) provide evidence suggesting market inefficiencies in the pricing of oil and gas firms in the 1979–1984 period. This...     

Combining long memory and level shifts in modelling and forecasting the volatility of asset returns

We propose a parametric state space model of asset return volatility with an accompanying estimation and forecasting framework that allows for ARFIMA dynamics, random level shifts and measurement errors. The Kalman filter is used to construct the state-augmented likelihood function and subsequently to generate forecasts, which are mean and path-corrected. We apply our model to eight daily volatility series constructed from both high-frequency and daily returns. Full sample parameter estimates reveal that random level shifts are present in all series. Genuine long memory is present in most high-frequency measures of volatility, whereas there is little remaining dynamics in the volatility measures constructed using daily returns. From extensive forecast evaluations, we find that our ARFIMA model with random level shifts consistently belongs to the 10% Model Confidence Set across a variety of forecast horizons, asset classes and volatility measures. The gains in forecast accuracy can be very pronounced, especially at longer horizons.     

Nonlinear effects of climate policy uncertainty and financial speculation on the global prices of oil and gas

With the acceleration of global energy transition and financialization, intense climate policy uncertainty and financial speculation have significant impacts on the global energy market. This paper uses TVP-VAR-SV models to analyze the nonlinear effects of climate policy uncertainty (CPU), financial speculation, economic activity, and US dollar exchange rate on global prices of crude oil and natural gas respectively, and then compare the time-varying response of oil prices and gas prices to six representative CPU peaks. The results show that responses of energy prices to various shocks have significant nonlinear effects: the time-varying effect of CPU on energy prices from positive to negative over time is significant, and financial speculation has the opposite effects on oil and gas prices. The effect from economic activity is mainly positive, while the effects of US dollar exchange are negative and stable. These results provide important implications for policymakers and investors dealing with high levels of climate policy uncertainty, financial speculation, and global economic activity.     

Log-normal continuous cascade model of asset returns: aggregation properties and estimation

Multifractal models and random cascades have been successfully used to model asset returns. In particular, the log-normal continuous cascade is a parsimonious model that has proven to reproduce most observed stylized facts. In this paper, several statistical issues related to this model are studied. We first present a quick, but extensive, review of its main properties and show that most of these properties can be studied analytically. We then develop an approximation theory in the limit of small intermittency λ²???1, i.e. when the degree of multifractality is small. This allows us to prove that the probability distributions associated with these processes possess some very simple aggregation properties across time scales. Such a control of the process properties at different time scales allows us to address the problem of parameter estimation. We show that one has to distinguish two different asymptotic regimes: the first, referred to as the ‘low-frequency asymptotics’, corresponds to taking a sample whose overall size increases, whereas the second, referred to as the ‘high-frequency asymptotics’, corresponds to sampling the process at an increasing sampling rate. The first case leads to convergent estimators, whereas in the high-frequency asymptotics, the situation is much more intricate: only the intermittency coefficient λ² can be estimated using a consistent estimator. However, we show that, in practical situations, one can detect the nature of the asymptotic regime (low frequency versus high frequency) and consequently decide whether the estimations of the other parameters are reliable or not. We apply our results to equity market (individual stocks and indices) daily return series and illustrate a possible application to the prediction of volatility and conditional value at risk.     

Misspecification of capital asset pricing: Empirical anomalies based on earnings' yields and market values

This study documents empirical anomalies which suggest that either the simple one-period capital asset pricing model (CAPM) is misspecified or that capital markets are inefficient. In particular, portfolios based on firm size or earnings/price (E/P) ratios experience average returns systematically different from those predicted by the CAPM. Furthermore, the ‘abnormal’ returns persist for at least two years. This persistence reduces the likelihood that these results are being generated by a market inefficiency. Rather, the evidence seems to indicate that the equilibrium pricing model is misspecified. However, the data also reveals that an E/P effect does not emerge after returns are controlled for the firm size effect; the firm size effect largely subsumes the E/P effect. Thus, while the E/P anomaly and value anomaly exist when each variable is considered separately, the two anomalies seem to be related to the same set of missing factors, and these factors appear to be more closely associated with firm size than E/P ratios.     

Disclosure of provisions for decommissioning costs in annual reports of oil and gas companies: A content analysis and stakeholder views

This study examines the extent of compliance with accounting disclosure requirements relating to provisions for decommissioning costs by oil and gas companies. We also investigate the views of stakeholders on the reporting practices of these companies. Using a content analysis approach, our findings reveal that compliance is substantially high, but companies tend to take a tick-box approach providing only minimum disclosure requirements. In semi-structured interviews, we find that disclosure decisions were driven by concerns about the credibility of information due to complexities in the accounting processes, regulatory requirements, lack of information demand and proprietary costs. These findings have policy implications.     

Cross-border spillover effects of unconventional monetary policies on Swiss asset prices

Unconventional monetary policies (UMPs) announced by the Federal Reserve, the European Central Bank, the Bank of England and the Bank of Japan exert important spillover effects on asset prices in Switzerland. Using a broad UMP event set and a long-term bond-futures based measure of market anticipation, we show that surprisingly expansionary UMPs lower Swiss government and corporate bond yields, induce the Swiss franc to appreciate, and dampen Swiss equity prices. Four extensions provide further insights. First, the estimated effects are strongest for announcements by the ECB. Second, the impact on government bonds is largest for bonds with residual maturities of 7–10 years. Third, the impact of foreign UMP shocks on exchange rates and Swiss bond yields is less pronounced after the introduction of the minimum rate of 1.20 Swiss franc per Euro by the Swiss National Bank on September 6, 2011, indicating that domestic monetary policy action partially affects the impact of external monetary shocks on domestic financial markets. Fourth, the sign of spillover effects differs for positive and negative UMP surprises, but their strength does not.     

上市公司财务参数与其股价波动性关系探究

本文探究了上市公司年度股价波动性与其上一年公开财务指标的相关关系。公开财务指标主要包括六项,从不同维度反映了公司规模、资本结构、偿债能力、盈利状况、管理状况和股东情况。通过分析结果发现,若干财务指标与上市公司的股价波动性都有显著的相关关系,大部分符合预期及常识。有一些财务指标与上市公司的股价波动性长时期内表现出稳定、显著的关系。文中尝试探讨了造成这种相关性的因素。