Short-term Uncertainty Research Articles

How does oil market uncertainty interact with other markets? An empirical analysis of implied volatility index

OVX (Crude oil volatility index), as a measure of oil market uncertainty and new volatility derivatives published by CBOE (Chicago Board Options Exchange) during the 2008 global financial crisis, provides a direct prediction of the market's expectation for future 30-day crude oil price volatility. This paper investigates the short- and long-term cross-market uncertainty transmission implied by OVX and other important volatility indices which are VIX (stock market volatility index), EVZ (euro/dollar exchange rate volatility index) and GVZ (gold price volatility index). The results indicate that there are no strong long-run equilibrium relationships among these volatility indices, which indirectly verify the effectiveness of cross-market volatility portfolio strategy for risk hedge. Furthermore, OVX is significantly influenced by other ones, which indicates that investors' volatility expectation in the oil market become more sensitive to uncertainty shocks from other markets when the global economic situation is extremely unstable. Finally, impacts of interior and exterior uncertainty shocks on OVX are found to be positive and transient. And the significant short-term uncertainty transmission between oil and other major markets has been confirmed.

Generation Expansion Planning Considering Mass Penetration of Renewable Energy Generation and Supply Reliability

SUMMARY In the future, renewable energy (RE) generation systems will be constructed and interconnected to the power system by nonutility entities such as generation companies and residential customers. Therefore, generation expansion planning (GEP) should consider the effects of RE generation. The purpose of this paper is to discuss the best GEP from the economic, supply reliability, and environmental aspects considering the penetration of RE generation. For this purpose, this paper proposes a model of a utility's GEP process considering RE generation. The proposed method is based on stochastic dynamic programming (SDP) in which long-term uncertainties are modeled by geometric Brownian motion (GBM) and the binomial lattice process. The variation of RE generation output due to the weather conditions (short-term uncertainty) is also considered in the proposed method by means of the net load curve.

Stadium attendance in German professional football – the (un)importance of uncertainty of outcome reconsidered

Although deeply ingrained in the economics of professional team sports literature, previous research could not confirm the importance of outcome uncertainty in European professional football. Moreover, a negative effect was detected and explained rather controversially: It is argued that the majority of spectators prefer to see the home team play either a much inferior team or a rather successful team. With data of n = 306 matches in the German Bundesliga, a generalized Tobit estimator with individual cut-off points and error terms clustered by home teams is employed to follow up with the discussion on the (un)importance of outcome uncertainty. The results highlight a significant positive effect on attendance when either the home and/or the away team still has a theoretical chance to win the championship while the suggested importance of teams still having the possibility to qualify for the UEFA Champions League is not supported (medium-term uncertainty). Furthermore, in line with previous research we could detect a negative effect of short-term uncertainty. However, while there is no evidence that spectators prefer the home team to play an inferior team, the results suggest that it is rather a strong brand of the away team that rises attendance figures in the German Bundesliga.

Operational verification of a framework for the probabilistic nowcasting of river discharge in small and medium size basins

Abstract. Forecasting river discharge is a very important issue for the prediction and monitoring of ground effects related to severe precipitation events. The meteorological forecast systems are unable to predict precipitation on small spatial (few km) and temporal (hourly) scales. For these reasons the issuing of reliable flood forecasts is not feasible in those regions where the basin's response to rainfall events is very fast and can generate flash floods. This problem can be tackled by using rainfall nowcasting techniques based on radar observations coupled with hydrological modeling. These procedures allow the forecasting of future streamflow with a few hours' notice. However, to account for the short-term uncertainties in the evolution of fine scale precipitation field, a probabilistic approach to rainfall nowcasting is needed. These uncertainties are then propagated from rainfall to runoff through a distributed hydrological model producing a set of equi-probable discharge scenarios to be used for the flood nowcasting with time horizons of a few hours. Such a hydrological nowcasting system is presented here and applied to some case studies. A first evaluation of its applicability in an operational context is provided and the opportunity of using the results quantitatively is discussed.

Wide-Area Measurement Based Dynamic Stochastic Optimal Power Flow Control for Smart Grids With High Variability and Uncertainty

To achieve a high penetration level of intermittent renewable energy, the operation and control of power systems need to account for the associated high variability and uncertainty. Power system stability and security need to be ensured dynamically as the system operating condition continuously changes. A wide-area measurement based dynamic stochastic optimal power flow (DSOPF) control algorithm using the adaptive critic designs (ACDs) is presented in this paper. The proposed DSOPF control replaces the traditional AGC and secondary voltage control, and provides a coordinated AC power flow control solution to the smart grid operation in an environment with high short-term uncertainty and variability. The ACD technique, specifically the dual heuristic dynamic programming (DHP), is used to provide nonlinear optimal control, where the control objective is explicitly formulated to incorporate power system economy, stability and security considerations. The proposed DSOPF controller dynamically drives the power system to its optimal operating point by continuously adjusting the steady-state set points sent by the traditional OPF algorithm. A 12-bus test power system is used to demonstrate the development and effectiveness of the proposed DSOPF controller.

Short-Term Return Continuation and Information Uncertainty: Evidence from the U.K. Market

Short-Term Return Continuation and Information Uncertainty: Evidence from the U.K. Market

The transitory and permanent volatility of oil prices: What implications are there for the US industrial production?

This study examines the impact of oil price uncertainty on the US industrial production by decomposing oil price volatility into permanent and transitory components. The decompositions provide important evidence on sources and asymmetric effects of oil price volatility. To estimate the component structure of volatility and to analyse the dynamic impacts of the volatility components, the study uses a threshold based CGARCH and VAR modelling over a period from 1980 to 2010 for the US economy. The CGARCH model estimates show significant asymmetric effect of oil price shock on the transitory oil price volatility. Dynamic impulse response functions obtained from the estimated VAR models reveal that there is a significant and prolonged dampening impact of increased transitory oil price volatility on industrial production. The results also suggest that shocks to transitory component induce increased volatility in the general price level and non-fuel commodity prices in the US. Variance decomposition analysis reconfirms that the transitory volatility is the second most important factor to explain the variance of industrial production. These results provide additional insights on the sources of oil price uncertainty and point to the need to direct US energy policies towards stabilising short-term uncertainties in oil prices.

Full Utilization of TWSTT Network Data for the Short-Term Stability and Uncertainty Improvement

The two-way satellite time and frequency transfer (TWSTFT) is a precise time transfer technique and has being used to generate the international atomic time since 1999. Nowadays, TWSTFT links have formed a worldwide network and the large amount of TWSTFT data become highly redundant. To fully utilize the data of TWSTFT network and improve the TWSTFT results, a feasible method of processing data is proposed in this paper. According to the stability of each link, we assign a weighting value to each related equation and then solve the matrix equation with the weighted least squares method. We perform data analysis with practical time transfer data, and the results show that it is an effective method to improve the short-term stabilities and uncertainties of TWSTFT results.

Too Good to Be True? An Analysis of the Options Market's Reactions to Earnings Releases

Using option implied risk neutral return distributions before and after earnings announcements, we study the option market's reaction to extreme events over earnings announcements. While earnings announcements generally reduce short term uncertainty about the stock price, very good news does not reduce uncertainty and slightly bad news actually increases uncertainty. Cross-sectional tests of realized volatility reductions are largely in line with option implied findings, except for cases where very good news is released, which suggests an irrational level of perceived uncertainty in options markets following very good news. We also find that left tail probabilities decrease over earnings releases while right tail probabilities increase. We interpret these findings as evidence of maintained investor expectations that very good news is generally not released during earnings announcements combined with unwarranted skepticism at the release of such news.

An institutional investor's perspective on oil and gas investment

From the perspective of an institutional oil and gas investor, investing is like creating a partnership. Given the long-term investment horizon, the focus is on creating value in the long run and on setting up the stage to withstand short-term volatility and uncertainty. A producer/developer is able to better focus on protecting its assets instead of managing the market’s expectations and quarterly earnings or KPIs. Also, projecting sub-surface performance is highly interpretive and adds another layer of risk to the already complex investment environment.

Supply chain design under uncertainty using sample average approximation and dual decomposition

We present a supply chain design problem modeled as a sequence of splitting and combining processes. We formulate the problem as a two-stage stochastic program. The first-stage decisions are strategic location decisions, whereas the second stage consists of operational decisions. The objective is to minimize the sum of investment costs and expected costs of operating the supply chain. In particular the model emphasizes the importance of operational flexibility when making strategic decisions. For that reason short-term uncertainty is considered as well as long-term uncertainty. The real-world case used to illustrate the model is from the Norwegian meat industry. We solve the problem by sample average approximation in combination with dual decomposition. Computational results are presented for different sample sizes and different levels of data aggregation in the second stage.

A digital open-loop Doppler processing prototype for deep-space navigation

A prototype based on digital radio technology with associated open-loop Doppler signal processing techniques has been developed to measure a spacecraft’s line-of-sight velocity. The prototype was tested in China’s Chang’E-1 lunar mission relying on S-band telemetry signals transmitted by the satellite, with results showing that the residuals had a RMS value of ∼3 mm/s (1 σ) using 1-sec integration, which is consistent with the Chinese conventional USB (Unified S-Band) tracking system. Such precision is mainly limited by the short-term stability of the atomic (e.g. rubidium) clock at the uplink ground station. It can also be improved with proper calibration to remove some effects of the transmission media (such as solar plasma, troposphere and ionosphere), and a longer integration time (e.g. down to 0.56 mm/s at 34 seconds) allowed by the spacecraft dynamics. The tracking accuracy can also be increased with differential methods that may effectively remove most of the long-term drifts and some of the short-term uncertainties of the uplink atomic clock, thereby further reducing the residuals to the 1 mm/s level. Our experimental tracking data have been used in orbit determination for Chang’E-1, while other applications (such as the upcoming YH-1 Mars orbiter) based on open-loop Doppler tracking will be initiated in the future. Successful application of the prototype to the Chang’E-1 mission in 2008 is believed to have great significance for China’s future deep space exploration.

Precise selenium isotope ratios measurement using a multimode sample introduction system (MSIS) coupled with multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS)

A multimode sample introduction hydride generation system (MSIS) was explored for rapid and precise measurements of Se isotope ratios. The MSIS system was modified in our laboratory in order to be coupled to the Neptune multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS) instrument. The principle aim of this study was focused on the optimization of the MSIS operating parameters for the determination of precise Se isotopic ratios measurements in environmental samples using the MC-ICP-MS as a detection system. Special attention has been paid to the performance of the MSIS system in dual mode operation “simultaneous nebulization and vapour (hydride) generation”. Typical internal (within-run) precision achieved under optimal conditions was better than 33 ppm (1 RSE) for 78Se/76Se, 78Se/77Se, 78Se/80Se and 78Se/82Se ratios using repeated measurements of NIST SRM 3149 Se standard solution. On average, the short-term uncertainty was better than 200, 150, 481 and 90 ppm (1 RSD) for 78Se/76Se, 78Se/77Se, 78Se/80Se and 78Se/82Se isotope ratios, respectively.

An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments

In this paper, we present a novel type-2 fuzzy systems based adaptive architecture for agents embedded in ambient intelligent environments (AIEs). Type-2 fuzzy systems are able to handle the different sources of uncertainty and imprecision encountered in AIEs to give a very good response. The presented agent architecture uses a one pass method to learn in a nonintrusive manner the user's particular behaviors and preferences for controlling the AIE. The agent learns the user's behavior by learning his particular rules and interval type-2 Membership Functions (MFs), these rules and MFs can then be adapted online incrementally in a lifelong learning mode to suit the changing environmental conditions and user preferences. We will show that the type-2 agents generated by our one pass learning technique outperforms those generated by genetic algorithms (GAs). We will present unique experiments carried out by different users over the course of the year in the Essex Intelligent Dormitory (iDorm), which is a real AIE test bed. We will show how the type-2 agents learnt and adapted to the occupant's behavior whilst handling the encountered short term and long term uncertainties to give a very good performance that outperformed the type-1 agents while using smaller rule bases

A stochastic dynamic model for optimal timing of investments in new generation capacity in restructured power systems

In this paper we formulate the power generation investment problem for a decentralised and profit-maximising investor operating in a restructured and competitive power system. In particular, we look at how uncertainty influences the optimal timing of investments in new power generation capacity. A real options approach is used to take long-term uncertainty in load growth, and its influence on future electricity prices, into account in the investment optimisation. In order to value the operational flexibility of a new power plant we use an electricity price model, where the spot price is a function of load level and installed generation capacity, in addition to short-term uncertainties and temporal fluctuations in the market. The investor’s income from a capacity payment, which also can depend on the system’s total capacity balance, can also be represented. Hence, with the optimisation model we can analyse power plant profitability and optimal timing of new investments under different market designs. In a case study from the Nordic electricity market we analyse the effect of uncertainty on optimal investment timing. We also examine how a fixed or variable capacity payment would influence the investment decision, and discuss the system consequences of the resulting investment strategies.

High-precision measurement of mercury isotope ratios in sediments using cold-vapor generation multi-collector inductively coupled plasma mass spectrometry

An on-line Hg reduction technique using stannous chloride as the reductant was applied for accurate and precise mercury isotope ratio determinations by multi-collector (MC)-ICP/MS. Special attention has been paid to ensure optimal conditions (such as acquisition time and mercury concentration) allowing precision measurements good enough to be able to significantly detect the anticipated small differences in Hg isotope ratios in nature. Typically, internal precision was better than 0.002% (1 RSE) on all Hg ratios investigated as long as approximately 20 ng of Hg was measured with a 10-min acquisition time. Introducing higher amounts of mercury (50 ng Hg) improved the internal precision to <0.001%. Instrumental mass bias was corrected using (205)Tl/(203)Tl correction coupled to a standard-sample bracketing approach. The large number of data acquired allowed us to validate the consistency of our measurements over a one-year period. On average, the short-term uncertainty determined by repeated runs of NIST SRM 1641d Hg standard during a single day was <0.006% (1 RSD) for all isotope pairs investigated ((202)Hg/(198)Hg, (202)Hg/(199)Hg, (202)Hg/(200)Hg, and (202)Hg/(201)Hg). The precision fell to <0.01% if the long-term reproducibility, taken over 11 months (over 100 measurements), was considered. The extent of fractionation has been investigated in a series of sediments subject to various Hg sources from different locations worldwide. The ratio (202)Hg/(198)Hg expressed as delta values (per mil deviations relative to NIST SRM 1641d Hg standard solution) displayed differences from +0.74 to -4.00 per thousand. The magnitude of the Hg fractionation per amu was constant within one type of sample and did not exceed 1.00 per thousand. Considering all results (the reproducibility of Hg standard solutions, reference sediment samples, and the examination of natural samples), the analytical error of our delta values for the overall method was within +/-0.28 per thousand (1 SD), which was an order of magnitude lower than the extent of fractionation (4.74 per thousand) observed in sediments. This study confirmed that analytical techniques have reached a level of long-term precision and accuracy that is sufficiently sensitive to detect even small differences in Hg isotope ratios that occur within one type of samples (e.g., between different sediments) and so far have unequivocally shown that Hg isotope ratios in sediments vary within approximately 5 per thousand.

Construction probabiliste de scénarios d'apports à un réservoir

The behaviour of a hydric system depends on three factors : (i) the state of the installation, (ii) the operating rules, and (iii) the inflows. While the first two factors are (in theory) known to the manager, the third can only be estimated by means of more or less precise forecasts. A significant part of the risk, to which is subjected the system at a given time, is induced by the uncertainty in the future inflows. The evaluation of this uncertainty is therefore a first step in the incorporation of risk into management. Its evaluation is then a stage preliminary to the integration of the risk in management. A method of construction of inflow scenarios starting from an arbitrary date t of the year is developed in this paper. It uses a Markovian process formerly developed by the authors to model short-term uncertainty in stream flow. These scenarios, which are not equiprobable, are built to reproduce the statistical behaviour of the river or reservoir and have the shape of an event tree whose structure is defined by the user before application of the method. Two examples of application on two rivers located in Quebec, Canada, are presented.Key words: reservoir operation, previsions, inflows, risk, uncertainty.

Short-Term Variations and Long-Term Dynamics in Commodity Prices

In this article, we develop a two-factor model of commodity prices that allows meanreversion in short-term prices and uncertainty in the equilibrium level to which prices revert. Although these two...

The outlook of the Korean petroleum industry and its deregulation process

This paper explores the outlook for the oil product supply and demand balance in Korea and the implications for future refinery market conditions. Forecasts of demand growth are compared with the industry's recent capacity expansion to evaluate potential future market positions. The possible impact of the current deregulation process, started in January 1977, is summarized. In addition, the short-term and long-term uncertainties of the market are discussed. The future business environment for refiners in Korea is likely to be tougher than expected. Although substantial new refining capacity was added recently, the demand for oil products is expected to increase less rapidly. The overall product balance and the threat of imports from outside the region indicate that refiners may suffer from a decrease in utilization rate. Challenges lie ahead if Korean oil refiners are to be part of a successful and mature industry.

Why Conflicts In The Former Soviet Union Are So Difficult To Negotiate And Mediate

AbstractThe difficulty in using negotiation and mediation to resolve conflicts in the former Soviet Union (FSU) derives from factors coming both from the Soviet and pre-Soviet Russian periods and from the current transition. Traditional reliance on authority and government centralization led to both reliance on and distrust of central authorities, neither of which is conducive to negotiation. In the transition period, rigidity, change, long-term and short-term uncertainty, distrust, and absence of valid spokespeople all contribute to undermine negotiations. Yet, inevitably, more negotiation and mediation will be needed and eventually used.