How does stock market volatility react to oil shocks?

We study the impact of oil price shocks on the U.S. stock market volatility. We jointly analyze three different structural oil market shocks (i.e., aggregate demand, oil supply, and oil-specific demand shocks) and stock market volatility using a structural vector autoregressive model. Identification is achieved by assuming that the price of crude oil reacts to stock market volatility only with delay. This implies that innovations to the price of crude oil are not strictly exogenous, but predetermined with respect to the stock market. We show that volatility responds significantly to oil price shocks caused by unexpected changes in aggregate and oil-specific demand, whereas the impact of supply-side shocks is negligible

STAR-GARCH Models for Stock Market Interactions in the Pacific Basin Region, Japan and US

We investigate the financial interactions between countries in the Pacific Basin region (Korea, Singapore, Malaysia, Hong Kong and Taiwan), Japan and US. The originality of the paper is the use of STAR-GARCH models, instead of standard correlation-cointegration techniques. For each country in the Pacific Basin region, we find statistically adequate STAR-GARCH models for the series of stock market daily returns, using Nikkei225 and S&P500 as alternative threshold variables. We provide evidence for the leading role of Japan in the period 1988-1990 (pre-Japanese crisis years), whereas our results suggest that the Pacific Basin region countries are more closely linked with the US during the period 1995-1999 (post- Japanese crisis years).STAR-GARCH models, stock market integration, Pacific-Basin capital markets, outliers

Exogenous Oil Shocks, Fiscal Policy and Sector Reallocations in Oil Producing Countries

Previous literature has suggested that different mechanisms of transmission of exogenous oil shocks are responsible for the negative effects on the economic performances of oil exporting countries. This paper aims at providing further evidence on the role of sectoral reallocation between private and public sectors in explaining the impact of shocks to oil revenues on the economic growth rates of major oil producing countries (namely the GCC - Gulf Corporation Council - countries). The effects of oil shocks and expansionary fiscal policy on the business cycle of oil producing countries are examined. The possibility to distinguish between various components of public sector spending policy (that is, purchases of consumption goods, investments in productive activities and compensation for public employees) is, in particular, allowed for. A real business cycle (RBC) model is calibrated to fit the data on an “average” oil producing country. Results from the simulation of the theoretical model suggest that the possibility that crowding-out effects of public over private investments can explain a large fraction of the negative effects of shocks to oil revenues on the private sector of the economy. In addition, since the growth in size of the public sector is unable to compensate for the reduction in size of the private sector, an increase in oil revenues has the effect to decrease total output. An expansionary fiscal policy is argued to have significant positive effects on private investments, employment and overall production. On the contrary, a shock to government consumption expenditure impacts negatively the level of public investment. As employment in the public sector increases significantly, public output responds positively to a shock in government consumption expenditure. Finally, an instantaneous negative effect on total investments and on the stock of capital in the economy is predicted. However, driven by the increase of the number of employees in the economy, total output expands.Oil Shocks, Dutch Disease, Resource Curse and Real Business Cycle Modelling

Econometric Models of Asymmetric Price Transmission

In this paper we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies which are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on the existence of price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long-run and short-run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Third, each empirical study is critically discussed in the light of this new classification of asymmetries. Fourth, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models.Price asymmetries, Cointegration, Partial adjustment, Threshold regime switching

Pricing and Hedging Illiquid Energy Derivatives:an Application to the JCC Index

In this paper we discuss a simple econometric strategy for pricing and hedging illiquid financial products, such as the Japanese crude oil cocktail (JCC) index, the most popular OTC energy derivative in Japan. First, we review the existing literature for computing optimal hedge ratios (OHR) and we propose a critical classification of the existing approaches. Second, we compare the empirical performance of different econometric models (namely, regression models in price-levels, price first differences, price returns, as well as error correction and autoregressive distributed lag models) in terms of their computed OHR using monthly data on the JCC over the period January 2000-January 2006. Third, we illustrate and implement a procedure to cross-hedge and price two different swaps on the JCC: a one-month swap and a three-month swap with a variable oil volume. We explain how to compute a bid/ask spread and to construct the hedging position for the JCC swap. Fourth, we evaluate our swap pricing scheme with backtesting and rolling regression techniques. Our empirical findings show that it is not necessary to use sophisticated econometric techniques, since the price level regression model permits to compute a more reliable optimal hedge ratio relative to its competing alternatives.Hedging Models, Cross-Hedging, Energy Derivatives, Illiquid Financial Products, Commodity Markets, JCC Price Index

Modelling the Load Curve of Aggregate Electricity Consumption Using Principal Components

Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compared with those produced by the Fourier and constrained smoothing spline estimators. The PC method represents a much simpler and attractive alternative to modelling electricity consumption since it is extremely easy to compute, it significantly reduces the number of variables to be considered, and generally increases the accuracy of electricity consumption forecasts. As an additional advantage, the PC method is able to accommodate relevant exogenous variables such as daily temperature and environmental factors, and it is extremely versatile in computing out-of-sample forecasts.Electricity, Load curves, Principal components, Fourier estimator, Constrained smoothing estimator, Temperature, Non-renewable resources, Hydrocarbon fuels, Environment

Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers

Call centers' managers are interested in obtaining accurate point and distributional forecasts of call arrivals in order to achieve an optimal balance between service quality and operating costs. We present a strategy for selecting forecast models of call arrivals which is based on three pillars: (i) flexibility of the loss function; (ii) statistical evaluation of forecast accuracy; (iii) economic evaluation of forecast performance using money metrics. We implement fourteen time series models and seven forecast combination schemes on three series of daily call arrivals. Although we focus mainly on point forecasts, we also analyze density forecast evaluation. We show that second moments modeling is important both for point and density forecasting and that the simple Seasonal Random Walk model is always outperformed by more general specifications. Our results suggest that call center managers should invest in the use of forecast models which describe both first and second moments of call arrivals

Modelling electricity prices: from the state of the art to a draft of a new proposal

In the last decades a liberalization of the electric market has started; prices are now determined on the basis of contracts on regular markets and their behaviour is mainly driven by usual supply and demand forces. A large body of literature has been developed in order to analyze and forecast their evolution: it includes works with different aims and methodologies depending on the temporal horizon being studied. In this survey we depict the actual state of the art focusing only on the recent papers oriented to the determination of trends in electricity spot prices and to the forecast of these prices in the short run. Structural methods of analysis, which result appropriate for the determination of forward and future values are left behind. Studies have been divided into three broad classes: Autoregressive models, Regime switching models, Volatility models. Six fundamental points arise: the peculiarities of electricity market, the complex statistical properties of prices, the lack of economic foundations of statistical models used for price analysis, the primacy of uniequational approaches, the crucial role played by demand and supply in prices determination, the lack of clearcut evidence in favour of a specific framework of analysis. To take into account the previous stylized issues, we propose the adoption of a methodological framework not yet used to model and forecast electricity prices: a time varying parameters Dynamic Factor Model (DFM). Such an eclectic approach, introduced in the late ‘70s for macroeconomic analysis, enables the identification of the unobservable dynamics of demand and supply driving electricity prices, the coexistence of short term and long term determinants, the creation of forecasts on future trends. Moreover, we have the possibility of simulating the impact that mismatches between demand and supply have over the price variable. This way it is possible to evaluate whether congestions in the network (eventually leading black out phenomena) trigger price reactions that can be considered as warning mechanisms.

On the Robustness of Robustness Checks of the Environmental Kuznets Curve

Since its first inception in the debate on the relationship between environment and growth in 1992, the Environmental Kuznets Curve has been subject to continuous and intense scrutiny. The literature can be roughly divided in two historical phases. Initially, after the seminal contributions, additional work aimed to extend the investigation to new pollutants and to verify the existence of an inverted-U shape as well as assessing the value of the turning point. The following phase focused instead on the robustness of the empirical relationship, particularly with respect to the omission of relevant explanatory variables other than GDP, alternative datasets, functional forms, and grouping of the countries examined. The most recent line of investigation criticizes the Environmental Kuznets Curve on more fundamental grounds, in that it stresses the lack of sufficient statistical testing of the empirical relationship and questions the very existence of the notion of Environmental Kuznets Curve. Attention is drawn in particular on the stationarity properties of the series involved – per capita emissions or concentrations and per capita GDP – and, in case of unit roots, on the cointegration property that must be present for the Environmental Kuznets Curve to be a well-defined concept. Only at that point can the researcher ask whether the long-run relationship exhibits an inverted-U pattern. On the basis of panel integration and cointegration tests for sulphur, Stern (2002, 2003) and Perman and Stern (1999, 2003) have presented evidence and forcefully stated that the Environmental Kuznets Curve does not exist. In this paper we ask whether similar strong conclusions can be arrived at when carrying out tests of fractional panel integration and cointegration. As an example we use the controversial case of carbon dioxide emissions. The results show that more EKCs come back into life relative to traditional integration/cointegration tests. However, we confirm that the EKC remains a fragile concept.Environment, Growth, CO2 Emissions, Panel data, Fractional integration, Panel cointegration tests