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Kiesel, Rüdiger, Florentina Paraschiv, and Audun Sætherø. "On the construction of hourly price forward curves for electricity prices." Computational Management Science 16, no. 1-2 (February 28, 2018): 345–69. http://dx.doi.org/10.1007/s10287-018-0300-6.
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MAISANO, J., A. RADCHIK, and T. LING. "A LOGNORMAL MODEL FOR DEMAND FORECASTING IN THE NATIONAL ELECTRICITY MARKET." ANZIAM Journal 57, no. 3 (January 2016): 369–83. http://dx.doi.org/10.1017/s1446181115000322.
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Many electricity market participants have a requirement to calculate the probabilistic risk measures, such as earnings at risk (EaR) and value at risk (VaR), for compliance reporting purposes. This requirement is currently hindered by the lack of analytical representations for forecasts of demand (load) and price curves; this motivates numerical simulation and models that need extensive calibration. In this paper, we derive an analytical representation of a state demand forecast which is the aggregated usage of all electricity consumers in a particular region (such as New South Wales or Victoria). We have used two probabilistic benchmarks from the Australian energy market operator as input, which are expressed as forecasted probability of exceedance.Due to a number of considerations, including asymmetry of these quantiles with respect to the median, we have selected a series of truncated lognormal distributions with two parameters. The procedure of finding these parameters has been reduced to solving (for every half-hour) a single nonlinear equation. As a result, the two-year half-hourly forecast (expected curve) and demand volatility are found by explicit integration with the set of derived distributions. We have also tested an alternative method based on simplifying assumptions; using a nontruncated lognormal distribution, we found that under the test conditions this method produces an identical forward load and volatility curve.
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Michelfelder, Richard A., and Eugene A. Pilotte. "Information in Electricity Forward Prices." Journal of Financial and Quantitative Analysis 55, no. 8 (October 29, 2019): 2641–64. http://dx.doi.org/10.1017/s0022109019000930.
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We examine forward prices in a market where nonstorable inventory exacerbates the influence of seasonal and hourly variation in supply and demand, expected and unexpected, on the level and volatility of spot prices. We find strong evidence, unusual for a commodity, that the difference between contemporaneous forward and spot prices has power to forecast both the spot price change and the risk premium realized at delivery. Our evidence of a time-varying risk premium is consistent with expected hourly and seasonal variation in the needs of producers and retailers of electricity to hedge against extreme spot price decreases and increases, respectively.
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Haugom, Erik, and Carl J. Ullrich. "Forecasting spot price volatility using the short-term forward curve." Energy Economics 34, no. 6 (November 2012): 1826–33. http://dx.doi.org/10.1016/j.eneco.2012.07.017.
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AIHARA, SHIN ICHI, and ARUNABHA BAGCHI. "IDENTIFICATION OF AFFINE TERM STRUCTURES FROM YIELD CURVE DATA." International Journal of Theoretical and Applied Finance 13, no. 02 (March 2010): 259–83. http://dx.doi.org/10.1142/s0219024910005760.
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We consider a slight perturbation of the Hull-White short rate model and the resulting modified forward rate equation. We identify the model coefficients by using the martingale property of the normalized bond price. The forward rate and the system parameters are then estimated by using the maximum likelihood method.
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Eberlein, Ernst, Christoph Gerhart, and Zorana Grbac. "Multiple curve Lévy forward price model allowing for negative interest rates." Mathematical Finance 30, no. 1 (March 14, 2019): 167–95. http://dx.doi.org/10.1111/mafi.12210.
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Eberlein, Ernst, and Christoph Gerhart. "A multiple-curve Lévy forward rate model in a two-price economy." Quantitative Finance 18, no. 4 (November 20, 2017): 537–61. http://dx.doi.org/10.1080/14697688.2017.1384558.
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Pontiggia, Dario. "Phillips curve and long-run inflation under commitment." Journal of Economic Studies 47, no. 1 (January 1, 2020): 21–35. http://dx.doi.org/10.1108/jes-06-2018-0229.
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PurposeThe purpose of this paper is to study the optimal long-run rate of inflation in the presence of a hybrid Phillips curve, which nests a purely backward-looking Phillips curve and the purely forward-looking New Keynesian Phillips curve (NKPC) as special limiting cases.Design/methodology/approachThis paper derives the long-run rate of inflation in a basic New Keynesian (NK) model, characterized by sticky prices and rule-of-thumb behavior by price setters. The monetary authority possesses commitment and its objective function stems from an approximation to the utility of the representative household.FindingsCommitment solution for the monetary authority leads to steady-state outcomes in which inflation, albeit small, is positive. Rising from zero under the purely forward-looking NKPC, the optimal long-run rate of inflation reaches its maximum under the purely backward-looking Phillips curve. In this case, inflation bias arises, while, under the hybrid Phillips curve, positive long-run inflation is associated with an output gain.Research limitations/implicationsThis paper serves as a clarification against the misperception that log-linearized models take as given the steady-state inflation rate rather than being capable of determining it. Analysis is sensitive to the basic NK setting, with the assumed rule-of-thumb behavior by price setters and price staggering.Originality/valueThe results are the first to quantify the optimal long-run rate of inflation in a fully microfounded model that nests different Phillips curves.
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Menyhért, B. "Estimating the Hungarian New-Keynesian phillips curve." Acta Oeconomica 58, no. 3 (September 1, 2008): 295–318. http://dx.doi.org/10.1556/aoecon.58.2008.3.3.
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This paper estimates the hybrid New-Keynesian Phillips curve (NKPC) for Hungary with different techniques. Because of weak instruments, single-equation GMM estimations yield very unreliable results. More robust methods show that basically no statistical inference is possible as to the true specification of the inflation dynamics. However, a more efficient simultaneous-equations method, the full information maximum likelihood (FIML) estimator provides identified parameters. Furthermore, coefficient estimates on the driving variable are positive and significant for the first time, lending much-needed empirical support in favour of the New-Keynesian model. Inflation appears to be determined to an equal extent by past inflation and forward-looking expectations. Structural analysis yields realistic estimates for the frequency of price adjustments and suggests that the dominant price setting behaviour is backward-looking.
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Fedorenko, I., G. Chornous, and V. Pylypchuk. "EVALUATION OF THE HYBRID NEW KEYNESIAN PHILLIPS CURVE FOR UKRAINE." Bulletin of Taras Shevchenko National University of Kyiv. Economics, no. 216 (2021): 64–73. http://dx.doi.org/10.17721/1728-2667.2021/216-3/8.
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The Hybrid New Keynesian Phillips Curve (HNKPC) was developed as a response to the apparent inertia in inflation the baseline New Keynesian Phillips curve leaved unexplained. Thus, the hybrid model combines two extreme cases – the traditional Phillips curve, and the purely forward-looking NKPC. The HNKPC also based on theoretical micro-foundations that aim to explain price stickiness and nominal rigidities. The paper is devoted to econometric testing and investigation the validity of the HNKPC (Calvo pricing model) for Ukraine. We use both the output gap and the marginal cost as the relevant indicators of real economic activity to determine the most appropriate one for Ukraine. Using the monthly data for the period 2016–2020, the main object is to compare the impact of both forward- and backward-looking components on inflation dynamic. Results of estimation by the Generalized Method of Moments (GMM) show that inflation possess resistant backward inertia due to domination of backwardlooking behaviour. Our findings indicate that the degree of price stickiness in Ukraine is found to be quite low, while the fraction of firms using the backward-looking rule in price setting is rather high. These estimates seem plausible from an economic point of view but not optimistic in terms of inflation targeting. The results provide useful insights for inflation dynamics and can be useful for improving monetary policy efficiency in Ukraine
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Hitzemann, Steffen, and Marliese Uhrig-Homburg. "Equilibrium Price Dynamics of Emission Permits." Journal of Financial and Quantitative Analysis 53, no. 4 (July 3, 2018): 1653–78. http://dx.doi.org/10.1017/s0022109018000297.
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This article presents a stochastic equilibrium model for environmental markets that allows us to study the characteristic properties of emission permit prices induced by the design of today’s cap-and-trade systems. We characterize emission permits as highly nonlinear contingent claims on economy-wide emissions and reveal their hybrid nature between investment and consumption assets. Our model makes predictions about the dynamics and volatility structure of emission permit prices, the forward price curve, and the implications for option pricing in this market. Empirical evidence from existing emissions markets shows that the model explains the stylized facts of emission permit prices and related derivatives.
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Jeon, Wooyoung, and Jungyoun Mo. "Estimating the Operating Reserve Demand Curve for Efficient Adoption of Renewable Sources in Korea." Energies 16, no. 3 (February 1, 2023): 1426. http://dx.doi.org/10.3390/en16031426.
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As the proportions of variable renewable sources (VRSs) such as solar and wind energy increase rapidly in the power system, their uncertainties inevitably undermine power supply reliability and increase the amount of operating reserve resources required to manage the system. However, because operating reserves have the characteristics of a public good and their value is related to the social cost of blackouts, it is difficult to determine their market price efficiently, which leads to inefficiencies in procuring operating reserves. This study estimates the operating reserve demand curve (ORDC) of the Korean power system to provide an effective basis for measuring the proper value and quantity of operating reserves needed to meet the reliability standard. A stochastic dynamic optimization model is applied to incorporate the probabilistic characteristics of VRS and the inter-hour constraint, which is necessary for analyzing load-following reserves. An econometric model and the Monte Carlo simulation method are used to generate the forecast profiles of solar and wind generation. The results indicate that the proper amount of hourly operating reserves needed in 2034 is approximately 4.4 times higher than that in 2020 at the current reserve offer price. The ORDC of 2020 has a price-inelastic shape, whereas the ORDC of 2034 has a price-elastic shape because the reserve requirement varies considerably with its offer price level in the high-VRS penetration case. This variability is due to alternatives, such as VRS curtailment or load shedding, which can replace the reserve requirement. This study also showed that VRS curtailment is an effective balancing resource as an alternative to reserves.
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ELLIOTT, ROBERT J., and ROGEMAR S. MAMON. "A COMPLETE YIELD CURVE DESCRIPTION OF A MARKOV INTEREST RATE MODEL." International Journal of Theoretical and Applied Finance 06, no. 04 (June 2003): 317–26. http://dx.doi.org/10.1142/s0219024903001852.
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This paper aims to present a complete term structure characterisation of a Markov interest rate model. To attain this objective, we first give a proof that establishes the Unbiased Expectation Hypothesis (UEH) via the forward measure. The UEH result is then employed, which considerably facilitates the calculation of an explicit analytic expression for the forward rate f(t, T). The specification of the bond price P(t, T), yield rate Y(t, T) and f(t, T) gives a complete set of yield curve descriptions for an interest rate market where the short rate r is a function of a continuous time Markov chain.
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PLATEN, ECKHARD. "AN ALTERNATIVE INTEREST RATE TERM STRUCTURE MODEL." International Journal of Theoretical and Applied Finance 08, no. 06 (September 2005): 717–35. http://dx.doi.org/10.1142/s0219024905003244.
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This paper proposes an alternative approach to the modeling of the interest rate term structure. It suggests that the total market price for risk is an important factor that has to be modeled carefully. The growth optimal portfolio, which is characterized by this factor, is used as reference unit or benchmark for obtaining a consistent price system. Benchmarked derivative prices are taken as conditional expectations of future benchmarked prices under the real world probability measure. The inverse of the squared total market price for risk is modeled as a square root process and shown to influence the medium and long term forward rates. With constant parameters and constant short rate the model already generates a hump shaped mean for the forward rate curve and other empirical features typically observed.
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Shu, Zhe, Shan Mei, and Wei Ping Wang. "The Game-Theoretic Approach to Pricing in China's Semi-Deregulated Electricity Market." Advanced Materials Research 805-806 (September 2013): 1116–21. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.1116.
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In Chinas semi-deregulated electricity market, a game-theoretic model has been set between users and power suppliers in order to ensure the whole network voltage load curve stay smooth, as well as to make the suppliers profitable on the basis of the satisfaction of users in power utilization in daily lives. The foundation of the model is the definition of the price elasticity of demand and its characters in micro-economy. According to this model, a Bayesian Nash equilibrium has been put forward based on the demand price elasticity, which can not only smooth the whole network voltage load curve effectively through the reciprocal process between users and power suppliers, but also can optimize the profit of the power suppliers. The simulation results of the voltage load curves and price changes graphs show the effectiveness of modeling simulation.
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ZHU, YINGZI, and JIN E. ZHANG. "VARIANCE TERM STRUCTURE AND VIX FUTURES PRICING." International Journal of Theoretical and Applied Finance 10, no. 01 (February 2007): 111–27. http://dx.doi.org/10.1142/s0219024907004123.
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Using no arbitrage principle, we derive a relation between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.
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Salunkhe, Bhavesh, and Anuradha Patnaik. "Inflation Dynamics and Monetary Policy in India: A New Keynesian Phillips Curve Perspective." South Asian Journal of Macroeconomics and Public Finance 8, no. 2 (August 28, 2019): 144–79. http://dx.doi.org/10.1177/2277978719861186.
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The present study estimates various specifications of the New Keynesian Phillips Curve (NKPC) models for India over 1996Q2 to 2017Q2 using Consumer Price Index (CPI) and Wholesale Price Index (WPI) inflation, separately. The empirical results suggest that the data support all the specifications of the Phillips curve models based on both the CPI and WPI inflations. However, the backward looking and hybrid models provide robust results for both the inflation indices. While the forward-looking behaviour dominates the CPI inflation trajectory, the backward-looking behaviour greatly influences the trajectory of WPI inflation. Also, a small-to-moderate degree of persistence is evident in both the CPI and WPI inflation. The output gap, which mainly represents the demand side pressures, turns up the major force determining both the CPI and WPI inflations. Besides the output gap, real effective exchange rate (reer), international crude oil price inflation, global non-fuel commodity price inflation and rainfall have a modest impact on the CPI and WPI inflations. JEL Classification: E12, E52, C36, C14
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Wardhono, Adhitya, M. Abd Nasir, Ciplis Gema Qori’ah, and Yulia Indrawati. "Movement of Inflation and New Keynesian Phillips Curve in ASEAN." Economies 9, no. 1 (March 10, 2021): 34. http://dx.doi.org/10.3390/economies9010034.
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The development of the theory of dynamic inflation begins by linking wage inflation and unemployment. In further developments, factor of expectation is classified into inflation model. The study used inflation data is important for ASEAN, because ASEAN is one of the strengths of the international economy. This study analyzes the dynamics of inflation in the ASEAN using framework the New-Keynesian Phillips Curve (NKPC) model. The data used is the quarterly panel data from 5 ASEAN members in the period 2005.QI–2018.QIV. The study of this dynamic inflation applies quarter to quarter inflation data, meaning that the inflation rate is the percentage change in the general price of the current quarter compared to last quarter general price divided by the last quarter. The empirical results are estimated by using the Generalized Method of Moment (GMM), both of the system and first different indicates that the pattern formation of inflation expectations are backward-looking and forward-looking. In addition, the estimated NKPC models show the backward-looking behavior is more dominant than the forward looking. Changes in inflation are not entirely influenced by expectations of inflation in each country. Changes in inflation are also influenced by the output gap, changes in money supply, and exchange rate. Based on the findings of this study, it can be concluded that the NKPC models can explain the dynamics of inflation in each country in the ASEAN region.
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Jiang, Jiheng, Ying Qiao, Zongxiang Lu, Liang Ran, Ming Ma, Jin Li, and Feng Wang. "Probabilistic evaluation of renewable energy curtailment under forward electricity market." E3S Web of Conferences 182 (2020): 02005. http://dx.doi.org/10.1051/e3sconf/202018202005.
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Forward electricity market has emerged as a pivotal section for the electricity transaction to keep stakeholders away from price risk and electricity shortage. But the forward contract of conventional unit partially limits the unit output before operation, leading to the curtailed generation share of renewable energy source (RES). Modeling and assessing this impact is of great significance for system planning and market supervision. The central thesis of this paper is to find out the impact of forward market on RES curtailment. A probabilistic evaluation model for RES accommodation is proposed, taking the curtailment rate as a main evaluation index. We mainly research financial contract and physical contract, modeling the impact of them on thermal unit minimum load capacity and power load in evaluation model. The simulation is conducted in a simplified system, which reveals the change of RES curtailment with renege penalty, contract price and execution generation curve.
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Dey, Bishwajit, Soham Dutta, and Fausto Pedro Garcia Marquez. "Intelligent Demand Side Management for Exhaustive Techno-Economic Analysis of Microgrid System." Sustainability 15, no. 3 (January 17, 2023): 1795. http://dx.doi.org/10.3390/su15031795.
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In a typical microgrid (MG) structure, the requisite of load varies from hour to hour. On the basis of the rise and fall of the load demand curve, the power system utilities fix the rate of electric power at different times of the day. This process is known as time-of-usage (TOU)-based pricing of electricity. The hourly basis load demand can be categorized into elastic hourly load demand and inelastic hourly load demand. For the duration of the peak hours, when the utility charges more, the elastic loads are shifted to low demand hours by the demand side management (DSM) to save the cost. This rebuilds the total demand model on the pillars of demand price elasticity. Keeping in view the fact that the total load in an hour in an MG structure consists of 10% to 40% of elastic loads, the paper proposes an intelligence-technique-based DSM to achieve reduction in the overall cost of using loads in an MG structure. Seven different cases are studied which cover diverse grid participation and electricity market pricing strategies, including DSM programs. The results obtained for all the MGs showcase the applicability and appropriateness of using the proposed DSM strategy in terms of cost savings.
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Rudd, Jeremy, and Karl Whelan. "Can Rational Expectations Sticky-Price Models Explain Inflation Dynamics?" American Economic Review 96, no. 1 (February 1, 2006): 303–20. http://dx.doi.org/10.1257/000282806776157560.
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The canonical inflation specification in sticky-price rational expectations models (the new-Keynesian Phillips curve) is often criticized for failing to account for the dependence of inflation on its own lags. In response, many studies employ a “hybrid” specification in which inflation depends on its lagged and expected future values, together with a driving variable such as the output gap. We consider some simple tests of the hybrid model that are derived from its closed form. We find that the hybrid model describes inflation dynamics poorly, and find little empirical evidence for the type of rational, forward-looking behavior that the model implies.
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Bundick, Brent, and A. Lee Smith. "The Dynamic Effects of Forward Guidance Shocks." Review of Economics and Statistics 102, no. 5 (December 2020): 946–65. http://dx.doi.org/10.1162/rest_a_00856.
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We examine the macroeconomic effects of forward guidance shocks at the zero lower bound. Empirically, we identify forward guidance shocks using unexpected changes in futures contracts around monetary policy announcements. We then embed these policy shocks in a vector autoregression to trace out their macroeconomic implications. Forward guidance shocks that lower expected future policy rates lead to moderate increases in economic activity and inflation. After examining forward guidance shocks in the data, we show that a standard model of nominal price rigidity can reproduce our empirical findings. To estimate our theoretical model, we generate a model-implied futures curve that closely links our model with the data. Our results suggest no disconnect between the empirical effects of forward guidance shocks around policy announcements and the predictions from a standard theoretical model.
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Casula, Laura, Guglielmo D’Amico, Giovanni Masala, and Filippo Petroni. "Performance estimation of photovoltaic energy production." Letters in Spatial and Resource Sciences 13, no. 3 (October 31, 2020): 267–85. http://dx.doi.org/10.1007/s12076-020-00258-x.
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AbstractThis article deals with the production of energy through photovoltaic (PV) panels. The efficiency and quantity of energy produced by a PV panel depend on both deterministic factors, mainly related to the technical characteristics of the panels, and stochastic factors, essentially the amount of incident solar radiation and some climatic variables that modify the efficiency of solar panels such as temperature and wind speed. The main objective of this work is to estimate the energy production of a PV system with fixed technical characteristics through the modeling of the stochastic factors listed above. Besides, we estimate the economic profitability of the plant, net of taxation or subsidiary payment policies, considered taking into account the hourly spot price curve of electricity and its correlation with solar radiation, via vector autoregressive models. Our investigation ends with a Monte Carlo simulation of the models introduced. We also propose the pricing of some quanto options that allow hedging both the price risk and the volumetric risk.
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Gáll, József, Gyula Pap, and Martien C. A. van Zuijlen. "Maximum likelihood estimator of the volatility of forward rates driven by geometric spatial AR sheet." Journal of Applied Mathematics 2004, no. 4 (2004): 293–309. http://dx.doi.org/10.1155/s1110757x04306133.
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Discrete-time forward interest rate curve models are studied, where the curves are driven by a random field. Under the assumption of no-arbitrage, the maximum likelihood estimator of the volatility parameter is given and its asymptotic behaviour is studied. First, the so-called martingale models are examined, but we will also deal with the general case, where we include the market price of risk in the discount factor.
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Brianzoni, Serena, Cristiana Mammana, Elisabetta Michetti, and Francesco Zirilli. "A Stochastic Cobweb Dynamical Model." Discrete Dynamics in Nature and Society 2008 (2008): 1–18. http://dx.doi.org/10.1155/2008/219653.
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We consider the dynamics of a stochastic cobweb model with linear demand and a backward-bending supply curve. In our model, forward-looking expectations and backward-looking ones are assumed, in fact we assume that the representative agent chooses the backward predictor with probability , and the forward predictor with probability , so that the expected price at time is a random variable and consequently the dynamics describing the price evolution in time is governed by a stochastic dynamical system. The dynamical system becomes a Markov process when the memory rate vanishes. In particular, we study the Markov chain in the cases of discrete and continuous time. Using a mixture of analytical tools and numerical methods, we show that, when prices take discrete values, the corresponding Markov chain is asymptotically stable. In the case with continuous prices and nonnecessarily zero memory rate, numerical evidence of bounded price oscillations is shown. The role of the memory rate is studied through numerical experiments, this study confirms the stabilizing effects of the presence of resistant memory.
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Chang, Yang-Ming, Joel M. Potter, and Shane Sanders. "Inelastic sports ticket pricing, marginal win revenue, and firm pricing strategy." Managerial Finance 42, no. 9 (September 12, 2016): 922–27. http://dx.doi.org/10.1108/mf-02-2016-0047.
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Purpose A standard result of firm theory is that a monopoly maximizes profit somewhere along the elastic portion of its demand curve. However, empirical studies of sports ticket pricing routinely find that (home) teams price along the inelastic portion of demand. Despite compelling theoretical explanations of this finding, at least one important factor remains unconsidered. A profit-maximizing team considers not only direct marginal revenue and direct marginal cost when setting a ticket price but also deferred, strategic benefit (revenue) from present game success. The paper aims to discuss these issues. Design/methodology/approach Prior literature finds that a given win is valued in that it generates additional future revenue and likelihood of home victory rises, ceteris paribus, in crowd density. The authors construct a firm profit maximization problem in which a sports team considers both present and future revenue when pricing home games in the present period. Findings If the deferred benefit is sufficiently large, a forward-looking, profit-maximizing team prices along the inelastic portion of its static demand curve. Importantly, this same price falls along the elastic portion of the firm’s (empirically unobserved) dynamic demand curve. Originality/value This is the first model of sports ticket pricing to recognize the intertemporal nature of demand for a sports match.
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Ulinuha, Agus, Hasyim Asy’ary, and Agus Supardi. "Enhancement of Electrical Distribution System Operation Using Intelligent Optimization Techniques Considering Unbalanced Condition." Applied Mechanics and Materials 660 (October 2014): 846–50. http://dx.doi.org/10.4028/www.scientific.net/amm.660.846.
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The enhancement of distribution system operation is proposed in this paper by optimally controlling the installed switchable devices. The objective of the control is to simultaneously minimize system losses and improve system voltage profile. This objective may be achieved by optimally dispatching the controllable components (shunt capacitor and Load Tap Changer/LTC) taking into account system unbalanced. A Genetic Algorithm (GA) is developed to determine the load curve partition useful for effective LTC scheduling and switching constraint satisfaction. GA is also assigned to determine the hourly status of shunt capacitor switching and LTC tap position. For power flow analyses under unbalanced conditions, Forward/Backward Propagation Algorithm is developed and employed. The strategy is implemented on the IEEE 34-bus unbalanced distribution system and the resulted improvement is analyzed. The main contribution is inclusion of unbalanced system conditions into optimization problem.
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Nurul, Muhammad, Syamsurijal Rasimeng, Ida Bagus Suananda Yogi, Aprillia Yulianata, and Aisah Yuliantina. "FORWARD MODELLING METODE GAYABERAT DENGAN MODEL INTRUSI DAN PATAHAN MENGGUNAKAN OCTAVE." JURNAL GEOCELEBES 4, no. 2 (September 23, 2020): 111–17. http://dx.doi.org/10.20956/geocelebes.v4i2.10112.
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The gravity method is a geophysical exploration method to measure variations in the acceleration of gravity on the surface of the earth in response to variations in rocks that exist beneath the surface. In gravity exploration requires a preliminary picture as a reference for measurement. This study aims to make forward modeling synthetic OCTAVE based using synthetic data on subsurface rock structures, so as to produce intrusion and fracture models based on differences in the value of the acceleration of gravity from one point to another on the surface of the earth. Synthetic modeling with the geological parameter approach of the study area is based on variations in the price of rock density. The model parameters used in intrusion modeling are the density value of 2.7 g/cm3 and the depth of 850 meters while the fracture modeling uses a density value of 2.7 g/cm3 with a depth of 350 meters and 360 meters and a thickness of 500 meters. From intrusion modeling, the gravity vertical component of attraction force is 0.03 mGal and in the fracture modeling the gravity vertical component of attraction force is 0.0565 mGal. Based on the results of this modeling, distance curve vs. gravity anomaly response is obtained for both cases. In the intrusion rock model obtained by the profile model with an open type down. While the fracture modeling is obtained anomalous profile curve variation which states that in the fracture area with a significant change in the direction of the curve.
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Guo, Ningxuan, Yinan Wang, Gangfeng Yan, and Jian Hou. "Non-Cooperative Game in Block Bidding Markets Considering Demand Response." Energies 13, no. 13 (June 29, 2020): 3322. http://dx.doi.org/10.3390/en13133322.
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With the reform of electricity markets, demand response (DR) plays an important role in providing flexibility to the markets. Block bidding market is a new market mode, which is based on the concept of “the same quality, the same price”. The mechanism has great effects in reducing start-stop related costs. In this paper, we propose a double-sided non-cooperative game model in block bidding markets with a DR program. The model combines the advantages of block bidding and the simplicity of hourly bidding. In the model, one side is the non-cooperative game of supply-side power firms, and we propose a novel supply function bidding model based on block duration and load capacity to maximize each firm’s profit. The other side is the demand-side different types of customers, and we propose a DR model that combines hourly-various prices with the block bidding mechanism to maximize each customer’s payoff. The overall market optimization problem is solved by a distributed iterative algorithm, which has great convergence performance. We verify the proposed model on real data, and the results show that the demand load curve becomes flattened with DR, and the total generation costs decrease while the social welfare is significantly improved.
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Meng, Yu, Baowen Li, Jingqiao Yang, Yong Wang, and Jianxun Niu. "Research on the Relationship Between Macroeconomic Indicators and Stock Market Value." Proceedings of Business and Economic Studies 5, no. 5 (October 26, 2022): 158–63. http://dx.doi.org/10.26689/pbes.v5i5.4243.
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The article first addresses the following questions: “Why does gross domestic product (GDP) rises, but the stock market value falls?”; “Among the macroeconomic factors, which factor has a greater impact on the promotion of investment value in the securities market?”. With these questions in mind, we put forward a hypothesis emphasizing on the impact of macroeconomic factors on the value of the stock market based on existing research and used the regression method to verify this hypothesis. The following conclusions were drawn: (1) variables that have a positive nonlinear relationship with stock market value include balance of payments surplus, rising GDP level, M1, the whole society’s fixed asset investment, and national per capita disposable income; (2) variables that have a negative nonlinear relationship with stock market value include deposit, loan interest rate, new RMB loan amount, consumer price index (CPI), and producer price index; (3) deposit reserve ratio has an S-shaped curve relationship with stock market value; (4) exchange rate has an inverted U-shaped curve relationship with stock market value.
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Tang, Huarong, and Yihong Xia. "An International Examination of Affine Term Structure Models and the Expectations Hypothesis." Journal of Financial and Quantitative Analysis 42, no. 1 (March 2007): 41–80. http://dx.doi.org/10.1017/s0022109000002180.
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AbstractWe examine the yield curve behavior and the relative performance of affine term structure models (ATSMs) using government bond yield data from Canada, Germany, Japan, the U.K., and the U.S. We find strong predictability of forward rates for excess bond returns and reject the expectations hypothesis in all five countries. A three-factor model is sufficient to capture movements in the yield curve of Canada, Japan, the U.K., and the U.S., but may not be enough for Germany. An exhaustive comparison among ATSMs with no more than three factors reveals that the three-factor essential affine model (A1(3)E), with only one factor affecting the volatility of the short rate but with all three factors affecting the price of risk, performs best in all five countries. Simulations provide inconclusive evidence on whether this best affine model can successfully generate the rich yield curve behavior observed in the data.
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Sinha, Rakesh, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai, and Hamidreza Zareipour. "Flexibility from Electric Boiler and Thermal Storage for Multi Energy System Interaction." Energies 13, no. 1 (December 24, 2019): 98. http://dx.doi.org/10.3390/en13010098.
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Active use of heat accumulators in the thermal system has the potential for achieving flexibility in district heating with the power to heat (P2H) units, such as electric boilers (EB) and heat pumps. Thermal storage tanks can decouple demand and generation, enhancing accommodation of sustainable energy sources such as solar and wind. The overview of flexibility, using EB and storage, supported by investigating the nature of thermal demand in a Danish residential area, is presented in this paper. Based on the analysis, curve-fitting tools, such as neural net and similar day method, are trained to estimate the residential thermal demand. Utilizing the estimated demand and hourly market spot price of electricity, the operation of the EB is scheduled for storing and fulfilling demand and minimizing energy cost simultaneously. This demonstrates flexibility and controlling the EB integrated into a multi-energy system framework. Results show that the curve fitting tool is effectively suitable to acknowledge thermal demands of residential area based on the environmental factor as well as user behaviour. The thermal storage has the capability of operating as a flexible load to support P2H system as well as minimize the effect of estimation error in fulfilling actual thermal demand simultaneously.
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Witzani, M., and P. Pechtl. "Modeling of (Cogeneration) Power Plants on Time-Dependent Power Demands of the Consumer." Journal of Engineering for Gas Turbines and Power 118, no. 2 (April 1, 1996): 353–58. http://dx.doi.org/10.1115/1.2816596.
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This paper presents a planning tool where rigorous plant performance models are used to produce accurate plant performance data reflecting real plant operation under the loads specified by load demand curves. Cumulative figures such as total fuel consumption and production efficiency serve as the basis for a subsequent detailed economic analysis. Basic inputs to the model are the energy demand curves for a specific site on a daily, hourly, or even per minute basis. The plant performance model takes into account the varying load levels, ambient conditions, fuel price, and revenues from electric power delivered off-site. The load/performance simulator calculates plant performance and basic economic parameters at each point in time of the load demand curve to exactly match the given energy demand (Fig. 1). The results are critical economic data like cumulated fuel consumption and expenses, total energy production, and overall averaged plant efficiency. The performance model delivers detailed plant performance data on an overall plant as well as component level. The results reflect real plant operation under all varying conditions, hence produce highly significant performance and economic parameters.
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Hongo, Duncan Omenda, Fanglin Li, and Max William Ssali. "Trade-Off Phillips Curve, Inflation and Economic Implication: The Kenyan Case." International Journal of Economics and Finance 11, no. 4 (March 15, 2019): 60. http://dx.doi.org/10.5539/ijef.v11n4p60.
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This paper investigated the trade-off and inflation drivers based on the Phillips curve framework to determine the relationship and their impact between inflation, unemployment and output for Kenyan case from 2006:M1 to 2016:M12 by contrasting the 2SLS on 2 different measures of marginal cost with 3 differently instrumented shocks. Results confirmed; (1) significant trade-off that reduced inflation by 2.09% and 0.08% when unemployment and output respectively increase by 1%, while, 1% increase in output demeaned unemployment by 0.02%, (2) the forward-looking inflation and unemployment significantly drive observed inflation, and (3) unlike monetary supply, oil shocks best accounts for the observed dynamics. Although laudable policies been implemented by fiscal and macro-economic planners, they have not achieved the odds to sufficiently contain the import shocks, making both unemployment and the rational expectations to significantly drive the observed inflation. However, revisiting of the incumbent fiscal policies and their tight implementation would facilitate long term price stabilities to reduce the inflationary dynamics. To the significant import shocks, the state should foster feasible macro-economic diversifications, investments policies, modern technologies in real economic activity production, and renewable energy sourcing that would facilitate robust economic growth that would curb large revenue outflows due to commodity imports and cushioning the devaluation of the Kenyan shilling.
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Chen, Baiping, Huifeng Wu, Hongwei Zhou, and Danfeng Sun. "EMP: Extended Kalman Filter Based Self-Adaptive Mold Protection Method on a Toggle Mechanism." Applied Sciences 10, no. 3 (January 31, 2020): 940. http://dx.doi.org/10.3390/app10030940.
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Nowadays, the plastic injection molding industry is ever-growing, crucial, and its plastic products can be seen everywhere. However, the mold damage problem still frustrates operators because of its high maintenance price and time-consuming maintenance process. This damage is commonly caused by foreign bodies in mold area, and the conventional mold protection method is insufficient for high-performance injection molding machines because of the uncertainty from many setting parameters. To improve detection precision of mold protection driven by a toggle mechanism ( T M ), this paper puts forward E M P , i.e., an extended Kalman filter ( E K F ) based self-adaptive mold protection method, wherein the E K F is used in current curve optimization, and the self-adaptive method ( S A M ) is proposed to gain an safety range of current curve. The E M P was verified in a 140-ton electric injection molding machine. Compared with a general method, the proposed method decreases the detected distance of mold protection by 22% under different thickness foreign bodies.
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Guo, Yuhang, Baozhi Pan, and Lihua Zhang. "A New Method to Identify Reservoirs in Tight Sandstones Based on the New Model of Transverse Relaxation Time and Relative Permeability." Geofluids 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/6787038.
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Relative permeability and transverse relaxation time are both important physical parameters of rock physics. In this paper, a new transformation model between the transverse relaxation time and the wetting phase’s relative permeability is established. The data shows that the cores in the northwest of China have continuous fractal dimension characteristics, and great differences existed in the different pore size scales. Therefore, a piece-wise method is used to calculate the fractal dimension in our transformation model. The transformation results are found to be quite consistent with the relative permeability curve of the laboratory measurements. Based on this new model, we put forward a new method to identify reservoir in tight sandstone reservoir. We focus on the Well M in the northwestern China. Nuclear magnetic resonance (NMR) logging is used to obtain the point-by-point relative permeability curve. In addition, we identify the gas and water layers based on new T2-Kr model and the results showed our new method is feasible. In the case of the price of crude oil being low, this method can save time and reduce the cost.
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Maekawa, Jun, and Koji Shimada. "A Speculative Trading Model for the Electricity Market: Based on Japan Electric Power Exchange." Energies 12, no. 15 (July 31, 2019): 2946. http://dx.doi.org/10.3390/en12152946.
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Renewable energy sources produce less environmental impact and have little marginal cost. Thus, because of these characteristics, it is desirable to disseminate it for the purpose of economic efficiency. Because of the uncertainty in the supply of renewable energy and the special feature of electricity as a good, such as merit order curve, introducing forward markets is an essential factor in a liberalized market. In European countries, which have already established several mechanisms for managing liquidity including markets with several timelines, the market liquidity invites the investor to perform some speculative action. We present a simple electric power market model to analyze the speculative actions of electricity suppliers and the price effect of such actions. Moreover, we found that the speculative action improves the inelasticity of the demand in electricity market.
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Pang, Jiaxing, Ningfei Wang, Xue Li, Xiang Li, Huiyu Wang, and Xingpeng Chen. "Impact of Economic Development Level and Agricultural Water Use on Agricultural Production Scale in China." International Journal of Environmental Research and Public Health 18, no. 17 (August 28, 2021): 9085. http://dx.doi.org/10.3390/ijerph18179085.
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The change of agricultural production scale is directly related to food security and the stable development of social economy. Particularly, the influence of economic development level and agricultural water use on agricultural production scale cannot be ignored. Therefore, this paper uses the fully modified ordinary least squares (FMOLS) and the Dumitrescu–Hurlin panel causality test models to discuss the effects of the level of economic development, agricultural water use, the level of urbanization, and the market price of agricultural products on the scale of agricultural production in China. The analysis results indicated that agricultural water use, the level of urbanization, and the market price of agricultural products promoted an increase of the scale of agricultural production at the total sample level; a 1% increase for these three variables will result in an increase of the scale of agricultural production of 0.634%, 0.377%, and 0.292%, respectively. The influence of economic development level on agricultural production scale accords with Kuznets curve. However, at the regional level, the influence of each variable on the eastern region is consistent with the trend of the total sample. In the central region, the impact of economic development on agricultural production scale shows a U-shaped curve, and the improvement of urbanization level inhibits the expansion of agricultural production scale. In the western region, all variables failed to pass the significance test. The results of the FMOLS model were validated by the fixed effects model. The results of causality tests showed that bidirectional causality existed between the scale of agricultural production and the level of economic development, the scale of agricultural production and agricultural water use, the level of economic development and the market price of agricultural products, and the level of urbanization and the market price of agricultural products. In different regions, there were differences in causality between variables. Therefore, based on the empirical results, we put forward some policy suggestions to maintain the scale of agricultural production.
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CHIARELLA, CARL, LES CLEWLOW, and BODA KANG. "THE EVALUATION OF MULTIPLE YEAR GAS SALES AGREEMENT WITH REGIME SWITCHING." International Journal of Theoretical and Applied Finance 19, no. 01 (February 2016): 1650005. http://dx.doi.org/10.1142/s0219024916500059.
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A typical gas sales agreement (GSA), also called a gas swing contract, is an agreement between a supplier and a purchaser for the delivery of variable daily quantities of gas, between specified minimum and maximum daily limits, over a certain number of years at a specified set of contract prices. The main constraint of such an agreement that makes them difficult to value is that in each gas year there is a minimum volume of gas (termed take-or-pay or minimum bill) for which the buyer will be charged at the end of the year (or penalty date), regardless of the actual quantity of gas taken. We propose a framework for pricing such swing contracts for an underlying gas forward price curve that follows a regime switching process in order to better capture the volatility behavior in such markets. With the help of a recombining pentanomial tree, we are able to efficiently evaluate the prices of the swing contracts, find optimal daily decisions and optimal yearly use of both the make-up bank and the carry forward bank at different regimes. We also show how the change of regime will affect the decisions.
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Yao, Leehter, Wei Lim, Sew Tiang, Teng Tan, Chin Wong, and Jia Pang. "Demand Bidding Optimization for an Aggregator with a Genetic Algorithm." Energies 11, no. 10 (September 20, 2018): 2498. http://dx.doi.org/10.3390/en11102498.
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Demand response (DR) is an effective solution used to maintain the reliability of power systems. Although numerous demand bidding models were designed to balance the demand and supply of electricity, these works focused on optimizing the DR supply curve of aggregator and the associated clearing prices. Limited researches were done to investigate the interaction between each aggregator and its customers to ensure the delivery of promised load curtailments. In this paper, a closed demand bidding model is envisioned to bridge the aforementioned gap by facilitating the internal DR trading between the aggregator and its large contract customers. The customers can submit their own bid as a pairs of bidding price and quantity of load curtailment in hourly basis when demand bidding is needed. A purchase optimization scheme is then designed to minimize the total bidding purchase cost. Given the presence of various load curtailment constraints, the demand bidding model considered is highly nonlinear. A modified genetic algorithm incorporated with efficient encoding scheme and adaptive bid declination strategy is therefore proposed to solve this problem effectively. Extensive simulation shows that the proposed purchase optimization scheme can minimize the total cost of demand bidding and it is computationally feasible for real applications.
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Rezaeimozafar, Mostafa, Mohsen Eskandari, Mohammad Hadi Amini, Mohammad Hasan Moradi, and Pierluigi Siano. "A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids." Energies 13, no. 7 (April 3, 2020): 1706. http://dx.doi.org/10.3390/en13071706.
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The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency.
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Boschee, Pam. "Comments: Staying Ahead of the Curve." Journal of Petroleum Technology 74, no. 01 (January 1, 2022): 8–9. http://dx.doi.org/10.2118/0122-0008-jpt.
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JPT’s editorial and production staff wish you the best in 2022! We are planning our year’s content to continue to bring you the latest deep technical insights and industry updates with an eye toward all disciplines. Our industry’s technology, goals, and business priorities are continually adjusting and changing. Our goal is to stay ahead of the curve. The editors of JPT, Oil and Gas Facilities, HSE Now, Data Science and Digital Engineering, and TWA work together to ensure our content provides SPE members with forward-thinking concepts, technologies, and applications to help you also stay ahead of the curve. We have you to thank for many of the ideas and technical expertise you share with us despite your own busy schedules and other commitments. Your time, effort, and willingness to share information are much appreciated. This issue of JPT debuts our refreshed design. We’ve made the presentation of the content “cleaner” and “easier on the eyes” by increasing the spacing of letters and lines of text, using two columns instead of three, and presenting graphics and captions more attractively. While we realize technical content does not demand “being pretty,” we also appreciate in our own reading how the creative presentation of content can be inviting. We’ve also changed the digital edition to a more user-friendly flipbook. When you move your cursor to the bottom of each page, you’ll see a toolbar where you can elect to zoom in or out, download the issue as a PDF to read offline, search within the issue, click to display the Table of Contents and click to go to a selected article, and view in full screen mode. If you prefer to read JPT on the website each month, you’ll continue to be able to do so when you log in. And, if you haven’t yet done so, follow JPT on LinkedIn to get our articles in your LinkedIn feed. Our industry is starting the year with a rebound and outlooks of guarded optimism. Wood Mackenzie’s Fraser McKay, vice president, upstream research, wrote in mid-December, “At a Brent price of around US$70/bbl, oil and gas cash flows will be at near-record levels. At US$80/bbl, it would soar towards US$1 trillion … Despite this, for many stakeholders and even some chief executives, the sector’s risks outweigh its upsides. This tension will define 2022.” The positive outlook will be tempered by concerns about its future as pressure grows to respond to COP26 pledges. In other words, 2022 is likely to deliver a mix of ups and downs. If you are the type who makes New Year’s resolutions (and remains committed to them), you are on your way to making changes, be they large or small. For others (like myself), resolutions fade all too quickly. But for all of us, a new year brings with it the anticipation of what lies ahead, be it joy or sorrow. Staying ahead of our own unpredictable curves professionally and personally is impossible, but the result is generally and thankfully a mix of highs and lows. Here’s to much more joy than sorrow, many more highs than lows.
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Song, Jie, Ting Wang, Yong Biao Yang, Xu Jieyan, Lu Chen, and Kun Huang. "Understanding of Demand Response in China and Automated Implementation." Applied Mechanics and Materials 373-375 (August 2013): 2278–83. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.2278.
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Demand response has great significance to the optimal adjustment of the electricity load curve, and also reduces difference between grid peak and valley load. But the promotion and implementation of demand response in China faces many aspects of problems such as electricity price control, power grid electricity sales profit mechanism and so on. Based on interpreting the classic electricity demand response theory, we consider the actual situation of China's electric power system and take a balance consideration of the interests of the government, power generation, power grid companies and electricity users, to give a new interpretation of the concept of demand response, which enriches technology means and economic means of demand response. Besides the leading role and main roles of implementation, we introduce the role of the initiator, and put forward the implementation of demand response project design and automated implementation system. This paper belongs to the national science and technology support programwith the power grid low carbonization characteristics of the smart grid integration technology research and demonstration in Jiangxi Provinceand SGCC projectWith the power grid low carbonization characteristics of the smart grid integration technology research and demonstration.
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Dinurrosifa, R. S., Sismindari, R. Rumiyati, and A. Rohman. "Duplex-real time polymerase chain reaction assay for simultaneous analysis of pork and chicken in sausage products." Food Research 4, no. 5 (June 30, 2020): 1767–72. http://dx.doi.org/10.26656/fr.2017.4(5).356.
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The adulteration of meat-based food is common due to the price difference among raw meat materials. One of the favorite foods commonly consumed by Indonesian and Malaysian societies is chicken sausage, which can be substituted by pork to get economical profits. The objective of this study was to develop a duplex real-time PCR assay using the EvaGreen fluorescence dye for the identification of chicken and pork in sausage products. The method involved the application of chicken (Gallus gallus) and pork (Sus scrofa) specific primers which amplify the small fragments (pork 176 bp and chicken 183 bp) of the mitochondrial D-loop 22 and mt-12s rRNA genes, respectively. DNA was isolated from raw meat materials and reference sausage made from the mixtures of chicken and pork to optimize the assay. The primers used for pork were forward 5’- TCG TAT GCA AAC CAA AAC GCC -3’ and reverse: 5’- ATG CAT GGG GAC TAG CAG TTA -3’, while primers used for chicken were forward: 5’ TGA GAA CTA CGA GCA CAA AC 3’ and reverse: 5’ ACA TTG TGG GAT CTT CTA GGT 3’. Gene products of chicken and pork produced two distinct melting peaks simultaneously at 76.5 and 84.5oC, respectively. The detection limit of duplex-real time PCR analysis of the reference sausage samples was 0.5% for pork and chicken meat in sausage products. The coefficient of variation (CV) of threshold cycles (Ct) for amplification was 6.25%, lower than that required by the Codex Alimentarius Commission. Duplex-real time PCR analysis followed by melting curve analysis offered rapid, sensitive, and specific detection of pork and chicken in sausage products.
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Yan, Bei, Weicong Ye, Juan Wang, Shaotong Jia, Xiuli Gu, Hao Hu, Wenpei Xiang, Tongbo Wu, and Xianjin Xiao. "Evaluation of Sperm DNA Integrity by Mean Number of Sperm DNA Breaks Rather Than Sperm DNA Fragmentation Index." Clinical Chemistry 68, no. 4 (February 1, 2022): 540–49. http://dx.doi.org/10.1093/clinchem/hvab280.
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Abstract Background Sperm DNA integrity is crucial for normal fertilization, implantation, and embryo development. Several assays are available to assess sperm DNA fragmentation but are limited by high price, complicated processes, and low accuracy. Methods We developed a secondary amplification detection system based on terminal deoxynucleotidyl transferase and endonuclease IV, which could efficiently measure the number of 3'-OH (equivalent to the number of breakpoints). We applied this detection system in single stranded DNA with standard concentrations to obtain the standard curve. We then broke the double stranded genomic DNA by ultrasound and enzyme digestion and used the detection system to monitor the increase of DNA breakpoints. Finally, we used this method to measure the mean number of sperm DNA breakpoints (MDB) in 80 sperm samples. Results We successfully measured the number of 3'-OH in single stranded DNA with standard concentration and obtained the standard curve. The linear range for the number of DNA breakpoints was from 0.1 nM to 15 nM. The detection method was successfully validated on λ DNA and 80 human sperm samples. The results of real clinical samples revealed that the mean number of DNA breakpoints (MDB) had a stronger relevance with the sperm motility and clinical pregnancy outcomes than the commonly used parameter of DNA fragmentation index (DFI). Conclusion We have developed a straight-forward method for direct measurement of the mean number of DNA breakpoints in sperms. The method has advantages of short time-consumption, simple operation, high analytical sensitivity, and low requirement for instrumentation, which makes it conducive to clinical application. The proposed new parameter (MDB) could be a more direct, accurate and clinically significant indicator for evaluating the sperm DNA integrity.
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VRINS, FRÉDÉRIC. "WRONG-WAY RISK CVA MODELS WITH ANALYTICAL EPE PROFILES UNDER GAUSSIAN EXPOSURE DYNAMICS." International Journal of Theoretical and Applied Finance 20, no. 07 (November 2017): 1750045. http://dx.doi.org/10.1142/s0219024917500455.
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We consider two classes of wrong-way risk models in the context of CVA: static (resampling) and dynamic (reduced form). Although both potentially suffer from arbitrage problems, their tractability makes them appealing to the industry and therefore deserve additional study. For example, Gaussian copula-based resampling and reduced-form with “Hull–White intensities” yield analytical expected positive exposure (EPE) profiles when the portfolio price process (i.e. exposure process) is Gaussian. However, the first approach disregards credit volatility whilst the second can provide default probabilities larger than 1. We therefore enlarge the study by introducing a new dynamic approach for credit risk, consisting in the straight modeling of the survival (Azéma supermartingale) process using the [Formula: see text]-martingale. This method is appealing in that it helps fixing some drawbacks of the above models. Indeed, it is a dynamic method (it disentangles correlation and credit volatility) that preserves probabilities in [Formula: see text] without affecting the analytical tractability of the model. In particular, calibration to any valid default probability curve is automatic and the closed-form expression for the EPE profiles remains available under Gaussian exposures. For each approach, we derive analytically the EPE profiles (conditional upon default) associated to prototypical exposure processes of Forward Rate Agreement (FRA) and Interest Rate Swap (IRS) in all cases and provide a comparison and discuss the implied Credit Valuation Adjustment (CVA) figures.
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Riederová, Sylvie. "Currency hedging with help of derivatives." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 59, no. 4 (2011): 273–80. http://dx.doi.org/10.11118/actaun201159040273.
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The high volatility combined with unpredictable fluctuations of CZK had shown one more time to the Czech exporting companies the necessity of currency hedging. This article is focused on finding of suitable currency hedging instrument for exporting company, working with the currency pair of CZK/EUR. In the first part, the time series analysis is made for volatility, interest rates and exchange rate. Based on the real market data – gained from Thomson REUTERS and CNB for the time period starting in 2002 – the detailed analysis is made in graphical form. The main goal is to find out the future trends with help of liner regression analysis, based on the historical data. Several graphs are provided with the trend line end estimated interval (min and max) for the each variable. The calculated values are clearly marked, to be separated from the real market data. Exchange rate curve shows the market behaviour in the last years and is to be used as most important indicator for the future trends. Interest rates curves are very important for the calculation of the BIPS (basis points), determining the price of the forwards. The difference between landing and deposit rates for the same period of time and different currencies are showing the market estimation of the future development of each currency. Forward price is to be seen as a benchmark for the all other financial instruments. And finally the volatility (quoted as middle) is very important part in the pricing of currency options.The second part is closely connected with the first one. Based on the results of provided analyses, it recommends a suitable hedging product for the next period of time. All of the analyses are taken as an input in different ways. The volatility is important for the decision of selling or purchasing the specific part of currency option. The exchange rate outlook together with the interest rates is the indicator of the future development of the currency pair and is playing the most important role in the decision process regarding the kind of hedging.
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Simshauser, Paul, and Jude Ariyaratnam. "What is normal profit for power generation?" Journal of Financial Economic Policy 6, no. 2 (May 6, 2014): 152–78. http://dx.doi.org/10.1108/jfep-09-2013-0045.
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Purpose – This paper aims to present a multi-period dynamic power project financing model to produce pragmatic estimates of benchmark wholesale power prices based on the principles of normal profit. This, in turn, can guide policymakers as to whether price spikes or bidding above marginal cost in wholesale electricity markets warrants any investigation at all. One of the seemingly complex areas associated with energy-only wholesale electricity pools is at what point market power abuse is present on the supply side. It should not be this way. If a theoretically robust measure of normal profit exists, identification of potential market power abuse is straightforward. Such a definition readily exists and can be traced back to the ground-breaking work of financial economists in the 1960s. Design/methodology/approach – Using a multi-period dynamic power project model, the authors produce pragmatic and theoretically robust measures of normal profit for project financed plant and plant financed on balance sheet. These model results are then integrated into a static partial equilibrium model of a power system. The model results are in turn used to guide policymaking on generator bidding in energy-only power markets. Findings – Under conditions of perfect plant availability and divisibility with no transmission constraints, energy-only markets result in clearing prices which are not economically viable in the long run. Bidding must, therefore, deviate from strict short-run marginal cost at some stage. To distinguish between quasi-contributions to substantial sunk costs and market power abuse, a pragmatic and robust measure of normal profit is required. Originality/value – This article finds policymakers can be guided by an ex-post analysis of base energy prices against pragmatic estimates for the long-run marginal cost of the base plant, and an ex-ante analysis of call option prices along the forward curve against pragmatic estimates of the carrying cost of the peaking plant.
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Lihui, Zhang, Xin He, and Ju Liwei. "A Multiobjective Scheduling Optimization Model for Multienergy Complementary System Integrated by Wind-Photovoltaic-Convention Gas Turbines considering Demand Response." Mathematical Problems in Engineering 2018 (July 31, 2018): 1–16. http://dx.doi.org/10.1155/2018/3208934.
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To utilize the complementary feature of different power sources, wind power plant (WPP), and solar photovoltaic power (PV), convention gas turbines (CGT) and incentive-based demand response (IBDR) are integrated into a multienergy complementary system (MECS) with the implementation of price-based demand response (PBDR). Firstly, the power output model of WPP, PV, and CGT is constructed and the mathematical model of DR is presented. Then, a multiobjective scheduling model is proposed for MECS operation under the objective functions of the maximum economic benefit, the minimum abandoned energy, and the minimum risk level. Thirdly, the payoff table of objective functions is put forward for converting the multiobjective model into a single objective model by using entropy weight method to calculate weighting coefficients of different objective functions. Finally, the improved IEEE 30 bus system is taken as the simulation system with four simulation scenarios for comparatively analyzing the influence of PBDR and IBDR on MECS operation. The simulation results show the following: (1) The MECS fully utilized the complementarity of different power sources; CGT and IBDR can provide peaking service for WPP and PV to optimize overall system operation. (2) The proposed algorithm can solve the MECS multiobjective scheduling optimization model, and the system scheduling results in the comprehensive optimal mode can take into account different appeal. And the total revenue, abandoned energy capacity, and load fluctuation are, respectively, 108009.30¥, 11.62 MW h, and 9.74 MW. (3) PBDR and IBDR have significant synergistic optimization effects, which can promote the grid connection of WPP and PV. When they are both introduced, the peak-to-valley ratio of the load curve is 1.19, and the abandoned energy is 5.85 MW h. Therefore, the proposed MECS scheduling model and solution algorithm could provide the decision basis for decision makers based on their actual situation.
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Derman, Emanuel, and Iraj Kani. "Stochastic Implied Trees: Arbitrage Pricing with Stochastic Term and Strike Structure of Volatility." International Journal of Theoretical and Applied Finance 01, no. 01 (January 1998): 61–110. http://dx.doi.org/10.1142/s0219024998000059.
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In this paper we present an arbitrage pricing framework for valuing and hedging contingent equity index claims in the presence of a stochastic term and strike structure of volatility. Our approach to stochastic volatility is similar to the Heath-Jarrow-Morton (HJM) approach to stochastic interest rates. Starting from an initial set of index options prices and their associated local volatility surface, we show how to construct a family of continuous time stochastic processes which define the arbitrage-free evolution of this local volatility surface through time. The no-arbitrage conditions are similar to, but more involved than, the HJM conditions for arbitrage-free stochastic movements of the interest rate curve. They guarantee that even under a general stochastic volatility evolution the initial options prices, or their equivalent Black–Scholes implied volatilities, remain fair. We introduce stochastic implied trees as discrete implementations of our family of continuous time models. The nodes of a stochastic implied tree remain fixed as time passes. During each discrete time step the index moves randomly from its initial node to some node at the next time level, while the local transition probabilities between the nodes also vary. The change in transition probabilities corresponds to a general (multifactor) stochastic variation of the local volatility surface. Starting from any node, the future movements of the index and the local volatilities must be restricted so that the transition probabilities to all future nodes are simultaneously martingales. This guarantees that initial options prices remain fair. On the tree, these martingale conditions are effected through appropriate choices of the drift parameters for the transition probabilities at every future node, in such a way that the subsequent evolution of the index and of the local volatility surface do not lead to riskless arbitrage opportunities among different option and forward contracts or their underlying index. You can use stochastic implied trees to value complex index options, or other derivative securities with payoffs that depend on index volatility, even when the volatility surface is both skewed and stochastic. The resulting security prices are consistent with the current market prices of all standard index options and forwards, and with the absence of future arbitrage opportunities in the framework. The calculated options values are independent of investor preferences and the market price of index or volatility risk. Stochastic implied trees can also be used to calculate hedge ratios for any contingent index security in terms of its underlying index and all standard options defined on that index.