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Journal articles on the topic 'Spot price model calibration'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

BARLOW, MARTIN, YURI GUSEV, and MANPO LAI. "CALIBRATION OF MULTIFACTOR MODELS IN ELECTRICITY MARKETS." International Journal of Theoretical and Applied Finance 07, no. 02 (2004): 101–20. http://dx.doi.org/10.1142/s0219024904002396.

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Spot prices of electricity and other energy commodities are often modeled by multifactor stochastic processes. This poses a problem of estimating models' parameters based on historical data, i.e. calibrating them to markets. Here we show how a traditional tool of Kalman Filters can be successfuly applied to do this task. We study two mean-reverting log-spot price models and the Pilipovic model using correspondingly Kalman Filter the extended Kalman Filter. The results of applying this method to market data from several power exchanges are discussed.

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2

HIKSPOORS, SAMUEL, and SEBASTIAN JAIMUNGAL. "ENERGY SPOT PRICE MODELS AND SPREAD OPTIONS PRICING." International Journal of Theoretical and Applied Finance 10, no. 07 (2007): 1111–35. http://dx.doi.org/10.1142/s0219024907004573.

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In this article, we construct forward price curves and value a class of two asset exchange options for energy commodities. We model the spot prices using an affine two-factor mean-reverting process with and without jumps. Within this modeling framework, we obtain closed form results for the forward prices in terms of elementary functions. Through measure changes induced by the forward price process, we further obtain closed form pricing equations for spread options on the forward prices. For completeness, we address both an Actuarial and a risk-neutral approach to the valuation problem. Finall

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3

Aiube, Fernando Antonio Lucena, and Ariel Levy. "Recent movement of oil prices and future scenarios." Nova Economia 29, no. 1 (2019): 223–48. http://dx.doi.org/10.1590/0103-6351/4159.

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Abstract The recent movement of oil prices has brought many forecasts about what is coming in the near future. This is natural since the plunge in prices has been dramatic after 2014 and oil is an essential source of energy worldwide. This paper examines the probabilities of spot price scenarios. We model prices through stochastic processes focusing on the Schwartz-Smith model. The calibration is based on the term structure of future prices. Since the conditional distribution is log-normal we define the probability of a certain value of the spot price in a given time horizon. We found that the

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Andrade, José R., Jorge Filipe, Marisa Reis, and Ricardo J. Bessa. "Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model." Sustainability 9, no. 11 (2019): 1990. https://doi.org/10.3390/su9111990.

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Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement

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FOUQUE, JEAN-PIERRE, YURI F. SAPORITO, and JORGE P. ZUBELLI. "MULTISCALE STOCHASTIC VOLATILITY MODEL FOR DERIVATIVES ON FUTURES." International Journal of Theoretical and Applied Finance 17, no. 07 (2014): 1450043. http://dx.doi.org/10.1142/s0219024914500435.

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In this paper, we present a new method for computing the first-order approximation of the price of derivatives on futures in the context of multiscale stochastic volatility studied in Fouque et al. (2011). It provides an alternative method to the singular perturbation technique presented in Hikspoors & Jaimungal (2008). The main features of our method are twofold: firstly, it does not rely on any additional hypothesis on the regularity of the payoff function, and secondly, it allows an effective and straightforward calibration procedure of the group market parameters to implied volatilitie

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Masala, Giovanni, Marco Micocci, and Andrea Rizk. "Hedging Wind Power Risk Exposure through Weather Derivatives." Energies 15, no. 4 (2022): 1343. http://dx.doi.org/10.3390/en15041343.

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We introduce the industrial portfolio of a wind farm of a hypothetical company and its valuation consistent with the financial market. Next, we propose a static risk management policy originating from hedging against volumetric risk due to drops in wind intensity and we discuss the consequences. The hedging effectiveness firstly requires adequate modeling calibration and an extensive knowledge of these atypical financial (commodity) markets. In this hedging experiment, we find significant benefits for weather-sensitive companies, which can lead to new business opportunities. We provide a new f

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Gonzalez, Jhonny, John Moriarty, and Jan Palczewski. "Bayesian calibration and number of jump components in electricity spot price models." Energy Economics 65 (June 2017): 375–88. http://dx.doi.org/10.1016/j.eneco.2017.04.022.

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Boukai, Benzion. "On the Class of Risk Neutral Densities under Heston’s Stochastic Volatility Model for Option Valuation." Mathematics 11, no. 9 (2023): 2124. http://dx.doi.org/10.3390/math11092124.

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The celebrated Heston’s stochastic volatility (SV) model for the valuation of European options provides closed form solutions that are given in terms of characteristic functions. However, the numerical calibration of this five-parameter model, which is based on market option data, often remains a daunting task. In this paper, we provide a theoretical solution to the long-standing ‘open problem’ of characterizing the class of risk neutral distributions (RNDs), if any, that satisfy Heston’s SV for option valuation. We prove that the class of scale parameter distributions with mean being the forw

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Gürtler, Marc, and Thomas Paulsen. "Forecasting performance of time series models on electricity spot markets." International Journal of Energy Sector Management 12, no. 4 (2018): 617–40. http://dx.doi.org/10.1108/ijesm-12-2017-0006.

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Purpose Study conditions of empirical publications on time series modeling and forecasting of electricity prices vary widely, making it difficult to generalize results. The key purpose of the present study is to offer a comparison of different model types and modeling conditions regarding their forecasting performance. Design/methodology/approach The authors analyze the forecasting performance of AR (autoregressive), MA (moving average), ARMA (autoregressive moving average) and GARCH (generalized autoregressive moving average) models with and without the explanatory variables, that is, power c

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Shao, Lingjie, and Kaili Xiang. "Valuation of Swing Options under a Regime-Switching Mean-Reverting Model." Mathematical Problems in Engineering 2019 (January 9, 2019): 1–14. http://dx.doi.org/10.1155/2019/5796921.

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In this paper, we study the valuation of swing options on electricity in a model where the underlying spot price is set to be the product of a deterministic seasonal pattern and Ornstein-Uhlenbeck process with Markov-modulated parameters. Under this setting, the difficulties of pricing swing options come from the various constraints embedded in contracts, e.g., the total number of rights constraint, the refraction time constraint, the local volume constraint, and the global volume constraint. Here we propose a framework for the valuation of the swing option on the condition that all the above

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Jędrzejewski, Arkadiusz, Grzegorz Marcjasz, and Rafał Weron. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO." Energies 14, no. 11 (2021): 3249. http://dx.doi.org/10.3390/en14113249.

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Recent studies suggest that decomposing a series of electricity spot prices into a trend-seasonal and a stochastic component, modeling them independently, and then combining their forecasts can yield more accurate predictions than an approach in which the same parsimonious regression or neural network-based model is calibrated to the prices themselves. Here, we show that significant accuracy gains can also be achieved in the case of parameter-rich models estimated via the least absolute shrinkage and selection operator (LASSO). Moreover, we provide insights as to the order of applying seasonal

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12

Di Francesco, Marco. "A General Gaussian Interest Rate Model Consistent with the Current Term Structure." ISRN Probability and Statistics 2012 (September 5, 2012): 1–16. http://dx.doi.org/10.5402/2012/673607.

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We describe an extension of Gaussian interest rate models studied in literature. In our model, the instantaneous spot rate is the sum of several correlated stochastic processes plus a deterministic function. We assume that each of these processes has a Gaussian distribution with time-dependent volatility. The deterministic function is given by an exact fitting to observed term structure. We test the model through various numeric experiments about the goodness of fit to European swaptions prices quoted in the market. We also show some critical issues on calibration of the model to the market da

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13

Alexander, Garcia Gaona Robinson, and Zapata Quimbayo Carlos Andres. "Multifactorial Heath-Jarrow-Morton model using principal component analysis." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (2024): 566–73. https://doi.org/10.11591/ijece.v14i1.pp566-573.

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In this study, we propose an implementation of the multifactor Heath-Jarrow- Morton (HJM) interest rate model using an approach that integrates principal component analysis (PCA) and Monte Carlo simulation (MCS) techniques. By integrating PCA and MCS with the multifactor HJM model, we successfully capture the principal factors driving the evolution of short-term interest rates in the US market. Additionally, we provide a framework for deriving spot interest rates through parameter calibration and forward rate estimation. For this, we use daily data from the US yield curve from June 2017 to Dec

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GLASSERMAN, PAUL, and QI WU. "FORWARD AND FUTURE IMPLIED VOLATILITY." International Journal of Theoretical and Applied Finance 14, no. 03 (2011): 407–32. http://dx.doi.org/10.1142/s0219024911006590.

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We address the problem of defining and calculating forward volatility implied by option prices when the underlying asset is driven by a stochastic volatility process. We examine alternative notions of forward implied volatility and the information required to extract these measures from the prices of European options at fixed maturities. We then specialize to the SABR model and show how the asymptotic expansion of the bivariate transition density in Wu (forthcoming) allows calibration of the SABR model with piecewise constant parameters and calculation of forward volatility. We then investigat

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15

Guerini, Alice, Andrea Marziali, and Giuseppe De Nicolao. "MCMC calibration of spot‐prices models in electricity markets." Applied Stochastic Models in Business and Industry 36, no. 1 (2019): 62–76. http://dx.doi.org/10.1002/asmb.2471.

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16

ANDRESEN, ARNE, FRED ESPEN BENTH, STEEN KOEKEBAKKER, and VALERIY ZAKAMULIN. "THE CARMA INTEREST RATE MODEL." International Journal of Theoretical and Applied Finance 17, no. 02 (2014): 1450008. http://dx.doi.org/10.1142/s0219024914500083.

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In this paper, we present a multi-factor continuous-time autoregressive moving-average (CARMA) model for the short and forward interest rates. This model is able to present an adequate statistical description of the short and forward rate dynamics. We show that this is a tractable term structure model and provides closed-form solutions to bond prices, yields, bond option prices, and the term structure of forward rate volatility. We demonstrate the capabilities of our model by calibrating it to a panel of spot rates and the empirical volatility of forward rates simultaneously, making the model

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17

Gao, Xia, and Zhanxing Zhao. "A Minimum Variance Hedging Ratio Model Based on Nonlinear Grey Classification Model." Wireless Communications and Mobile Computing 2022 (February 28, 2022): 1–8. http://dx.doi.org/10.1155/2022/9848223.

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The risk transfer function of futures market is mainly realized by hedging strategy. Futures price yield and spot price yield tend to show different fluctuations before and during hedging, which leads to the distortion of hedging ratio, that is, the calculated hedging effect is weaker than the traditional hedging effect. On the basis of MV (minimum variance) hedging model, this paper introduces NGCM (nonlinear grey classification model) to solve the nonlinear correlation between futures and spot returns, which can improve the hedging effect. The results show that, due to the existence of basis

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18

Wu, Sen, Shuaiqi Liu, Huimin Zong, Yiyuan Sun, and Wei Wang. "Research on a Prediction Model and Influencing Factors of Cross-Regional Price Differences of Rebar Spot Based on Long Short-Term Memory Network." Sustainability 15, no. 6 (2023): 4951. http://dx.doi.org/10.3390/su15064951.

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In this paper, taking rebar steel as an example, we study the causes and influencing factors of spot price differences in rebar steel in different regions, and put forward a prediction model of rebar steel regional price differences based on the spot price of rebar from 2013 to 2022, supply and demand, cost, macroeconomics, industrial economic indicators, and policy data. Through correlation analysis, we consider all influencing factors step by step, select indicators with high correlation to add to the model, and select the optimal combination of influencing factors by comparing the results o

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Ye, Minghua, Rongming Wang, Guozhu Tuo, and Tongjiang Wang. "Crop price insurance in China: pricing and hedging using futures market." China Agricultural Economic Review 9, no. 4 (2017): 567–87. http://dx.doi.org/10.1108/caer-12-2015-0178.

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Purpose The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market. Design/methodology/approach Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market. Findings The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, a

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20

Naipunya, J., I. Bhavani Devi, and D. Vishnusankar Rao. "Efficiency of chilli futures trading in terms of price discovery and price transmission." INTERNATIONAL RESEARCH JOURNAL OF AGRICULTURAL ECONOMICS AND STATISTICS 11, no. 2 (2020): 137–43. http://dx.doi.org/10.15740/has/irjaes/11.2/137-143.

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This paper has examined the efficiency of futures trading of chilli in terms of price discovery and transmission. Seemingly unrelated regression” (SUR) model, Johansen’s multiple cointegrationtest, granger causality test and vector error correction model was applied to draw the results. Chilli spot market (Guntur) was efficient in price discovery. The Silbers and Garbage value of futures market was 0.0403 being significant at 1 per cent level (0.0037) indicating that futures market of chilli was inefficient in price discovery. The findings of the ADF test suggested that futures and spot prices

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21

Helbawanti, Octaviana, and Masyhuri -. "Volatility and Market Integration of Spot-Forward Corn Price in Indonesia." Media Trend 14, no. 1 (2019): 1–9. http://dx.doi.org/10.21107/mediatrend.v14i1.4379.

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This study aims to determine the volatility and market integration between the price of corn in the Indonesian spot market and futures market in the international market. The data used in this research is secondary data consisting of Indonesian corn spot price and corn forward price referring commodity exchange, Chicago. Data in the form of monthly time series in 2007 until 2016. ARCH / GARCH method is used to measure the volatility at spot and forward price, whereas the market integration of spot and forward corn is used Johansen Cointegration and Engel-Granger Causality method. The results s

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22

Xin, He, and Zhang Guofu. "Dynamic Nonlinear Correlation Studies on Stock and Oil Market Based on Copula." Open Petroleum Engineering Journal 8, no. 1 (2015): 405–9. http://dx.doi.org/10.2174/1874834101508010405.

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Employing the dataset of WTI oil spot price and stock price index in China，Brazil, India, US, German, France, UK and Japan, this paper obtains five subintervals of whole sample range through a nonparametric multiple change point algorithms. Furthermore, it analyzes dependence between oil spot price and stock price index through copula model and computes the value of VaR and ES based on simulation for every subinterval. It reveals that dependence between oil spot price and stock price index during financial crisis is an asymmetric tail dependence. The value of VaR and ES of the oil spot price a

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23

Da Silva Leite, André Luis, and Marcus Vinicius Andrade de Lima. "A GARCH Model to Understand the Volatility of the Electricity Spot Price in Brazil." International Journal of Energy Economics and Policy 13, no. 5 (2023): 332–38. http://dx.doi.org/10.32479/ijeep.14226.

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Electricity is sensitive to extreme price events and spot price volatility is an inherent characteristic of competitive electricity markets. The purpose of this article it to model the realized volatility of electricity spot price in Brazil. The Brazilian electricity industry presents unique characteristics and because of this price varies a lot in a short period. So, we developed a GARCH model using 862 weekly observations to understand the realized volatility in the four different market. We conclude that the spot price in Brazil presents high volatility that presents risk to agents. This hi

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Kumar Mahalik, Mantu, Debashis Acharya, and M. Suresh Babu. "Price discovery and volatility spillovers in futures and spot commodity markets." Journal of Advances in Management Research 11, no. 2 (2014): 211–26. http://dx.doi.org/10.1108/jamr-09-2012-0039.

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Purpose – The purpose of this paper is to investigate empirically the price discovery and volatility spillovers in Indian spot-futures commodity markets. Design/methodology/approach – The study has used four futures and spot indices of Multi-Commodity Exchange, Mumbai. The study also employs vector error correction model (VECM) and bivariate exponential Garch model (EGARCH) to analyze the price discovery and volatility spillovers in Indian spot-futures commodity market. Findings – The VECM shows that agriculture future price index (LAGRIFP), energy future price index (LENERGYFP) and aggregate

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Wang, Lei, Min Wei, Heng Yang, Jinxian Li, Sainan Li, and Yunzhi Fei. "Optimization Model of Electricity Spot Market Considering Pumped Storage in China." Journal of Physics: Conference Series 2401, no. 1 (2022): 012041. http://dx.doi.org/10.1088/1742-6596/2401/1/012041.

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Abstract As China’s electricity market continues to evolve, pumped hydro storage will participate in electricity spot market transactions. According to the latest price policy of pumped storage, pumped storage units will not participate in the spot market bidding for a long time and will be settled at the spot price. Aiming at maximizing the welfare of the whole society, this paper proposes a full dispatch model for pumped storage units to participate in China’s electricity spot market under the new power system. By transforming the day-ahead spot market clearing results into the boundary cond

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Yan, Yunxian, Lu Tian, and Yuejie Zhang. "Is Chinese or American maize price effective for trading and policy-making reference?" China Agricultural Economic Review 6, no. 3 (2014): 470–84. http://dx.doi.org/10.1108/caer-05-2013-0080.

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Purpose – The purpose of this paper is to discover an effective maize price for trading and policy-making reference by assessing the price transmission of the US spot and futures maize prices to Chinese counterparts. Design/methodology/approach – The authors apply a systematic, quantitative method to analyze the integration between US and Chinese maize markets. Based on the residuals of the variables through error correction model, the directed acyclic graph (DAG) among six price variables is conducted. With consideration of the dependence on and direction of six price variables, the variance

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BJÖRK, TOMAS, MAGNUS BLIX, and CAMILLA LANDÉN. "ON FINITE DIMENSIONAL REALIZATIONS FOR THE TERM STRUCTURE OF FUTURES PRICES." International Journal of Theoretical and Applied Finance 09, no. 03 (2006): 281–314. http://dx.doi.org/10.1142/s0219024906003639.

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We consider HJM type models for the term structure of futures prices, where the volatility is allowed to be an arbitrary smooth functional of the present futures price curve. Using a Lie algebraic approach we investigate when the infinite dimensional futures price process can be realized by a finite dimensional Markovian state space model, and we give general necessary and sufficient conditions, in terms of the volatility structure, for the existence of a finite dimensional realization. We study a number of concrete applications including a recently developed model for gas futures. In particul

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SEDANA, WIRYA, KOMANG DHARMAWAN, and NI MADE ASIH. "MENENTUKAN HARGA KONTRAK BERJANGKA KOMODITAS KEDELAI MENGGUNAKAN MODEL MEAN REVERSION." E-Jurnal Matematika 5, no. 4 (2016): 170. http://dx.doi.org/10.24843/mtk.2016.v05.i04.p137.

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It has been discussed in many literatures that commodity prices tend to follow mean reversion model. This means that when there is a jump price in certain time, the price will revert to the mean price in the future. In this research, the method to determine the existence of mean-reversion of soybean price dynamics is discussed. Then, the future contract of soybeans is calculated using mean-reversion simulation and the spot-future parity theorem. Both methods are applied to the closing price of soybeans for the period of 19 September 2011 to 28 April 2016. The results show that the future contr

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Green, Hilary, Nino Kordzakhia, and Ruben Thoplan. "A Bivariate Model for Deman and Spot Price of Electricity." Advanced Materials Research 433-440 (January 2012): 3910–17. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3910.

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In this paper bivariate modelling methodology, solely applied to the spot price of electricity or demand for electricity in earlier studies, is extended to a bivariate process of spot price of electricity and demand for electricity. The suggested model accommodates common idiosyncrasies observed in deregulated electricity markets such as cyclical trends in price and demand for electricity, occurrence of extreme spikes in prices, and mean-reversion effect seen in settling of prices from extreme values to the mean level over a short period of time. The paper presents detailed statistical analysi

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Garg, Sonia, and Karam Pal Narwal. "Price Discovery and Volatility Spillover: An Empirical Analysis of Indian Futures-Spot Cardamom Markets." Journal of Commerce and Accounting Research 13, no. 2 (2024): 77–86. http://dx.doi.org/10.21863/jcar/2024.13.2.007.

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Price discovery and its related volatility spillover effect are significant indicators in commodity derivatives market to hedge the risk against sharp price fluctuations. This study empirically analyses the price discovery and volatility spillover using vector error correction model, Granger causality and bivariate exponential GARCH model (EGARCH) in Indian cardamom spot-futures markets. Daily time series data of spot market and near month futures contracts spanning the period from January 2009 to December 2020 have been used for the study. These price series data are based on the authenticate

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Crespi, John M., and Tian Xia. "A Note on First-Price Sealed-Bid Cattle Auctions in the Presence of Captive Supplies." Agricultural and Resource Economics Review 44, no. 3 (2015): 340–45. http://dx.doi.org/10.1017/s1068280500005098.

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The authors present an analytical model of a first-price sealed-bid cattle auction in which a spot and coordinated markets are interconnected. The model reveals that the conventional wisdom that market coordination negatively affects the bid price in the spot market is an oversimplification. The relationships between key market variables impact bids and bid shading in complex ways. While captive supplies can lead to lower spot prices, the price reductions do not necessarily stem from an increase in market power due to contracting. The model emphasizes the importance of several variables for fu

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FENG, JIANFEN, XIAOWEI HUANG, JUYUE HOU, CHUNXIA WANG, and YAN ZENG. "CARBON BOND PRICING AND MODEL SELECTION." Singapore Economic Review 63, no. 02 (2018): 465–81. http://dx.doi.org/10.1142/s0217590817400215.

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This paper discusses how to value a carbon bond and how to choose models for it like CGNPC wind additional carbon benefits of medium-term notes, the first Carbon-bond in China. First, the fractional process with jumps is used to model CERs spot price in BlueNext market and to price a numerical carbon bond. Then, through sensitive analysis for model parameters, the fractional process without jumps is suggested to model CERs spot price finally, but the fractional process with jumps may be more suitable for EA in China. Furthermore, there also discusses how to choose discount rate for those deriv

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BENTH, FRED ESPEN, and JŪRATĖ ŠALTYTĖ-BENTH. "THE NORMAL INVERSE GAUSSIAN DISTRIBUTION AND SPOT PRICE MODELLING IN ENERGY MARKETS." International Journal of Theoretical and Applied Finance 07, no. 02 (2004): 177–92. http://dx.doi.org/10.1142/s0219024904002360.

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We model spot prices in energy markets with exponential non-Gaussian Ornstein–Uhlenbeck processes. We generalize the classical geometric Brownian motion and Schwartz' mean-reversion model by introducing Lévy processes as the driving noise rather than Brownian motion. Instead of modelling the spot price dynamics as the solution of a stochastic differential equation with jumps, it is advantageous from a statistical point of view to model the price process directly. Imposing the normal inverse Gaussian distribution as the statistical model for the Lévy increments, we obtain a superior fit compare

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Fahria, Izma, Desy Yuliana Dalimunthe, Ririn Amelia, Ineu Sulistiana, and Baiq Desy Aniska Prayanti. "Prediksi Spot Price Komoditas Emas Berjangka dengan Pendekatan Vector Error Correction Model." Jambura Journal of Mathematics 5, no. 2 (2023): 339–50. http://dx.doi.org/10.34312/jjom.v5i2.18737.

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Time series data usually exhibit non-stationary behavior and involve interrelated variables. Thus, we need a model that can obtain good forecasting results from non-stationary time series data with multivariate variables. The Vector Error Correction Model (VECM) is a multivariate time series model which is a vector form of Vector Autoregressive Regression (VAR) for time series data that are non-stationary and have a cointegration relationship. This research was conducted to model the cointegration relationship in providing clarity on the long-term relationship of the influence of future prices

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Kang, Seok-Kyu. "A Study on the Price Discovery in Korea Stock Index Markets: KODEX200, KOSPI200, and KOSPI200 Futures." Journal of Derivatives and Quantitative Studies 17, no. 3 (2009): 67–97. http://dx.doi.org/10.1108/jdqs-03-2009-b0003.

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This paper examines the price discovery process among the Korea stock index markets using the vector error correction model (VECM) and the multivariate generalized auto regressive conditional heteroskedasticity (M-GARCH) model. The minute-by-minute price series of the KOSPI200 index, KOSPI200 futures, and KODEX200 are cointegrated. The empirical results are summarized as follows: First, VECM estimation results indicate that when the cointegrating relationship is perturbed by the arrival of ntis, the KODEX200(ETF) does not adjusted to restore equilibrium. This is the task of the KOSPI200 future

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Urretavizcaya Uranga, Gaizka, Maialen Areitioaurtena Oiartzun, Mario Javier Cabello, Carlos Molpeceres, and Miguel Morales. "General Methodology for Laser Welding Finite Element Model Calibration." Processes 12, no. 12 (2024): 2687. http://dx.doi.org/10.3390/pr12122687.

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Laser welding has become increasingly popular in recent decades due to its high processing speed and minimal heat-affected zone, which contribute to extended component lifetimes. However, the adoption of this advanced technique is often hindered by a lack of skilled personnel associated with traditional welding and limited awareness of its potential. This study proposes a straightforward methodology for developing a finite element-based thermal model for laser welding, incorporating a two-step experimental calibration process. Using temperature measurements from thermocouples and data from a w

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Benth, F. E., and L. Vos. "Pricing of Forwards and Options in a Multivariate Non-Gaussian Stochastic Volatility Model for Energy Markets." Advances in Applied Probability 45, no. 2 (2013): 572–94. http://dx.doi.org/10.1239/aap/1370870130.

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In Benth and Vos (2013) we introduced a multivariate spot price model with stochastic volatility for energy markets which captures characteristic features, such as price spikes, mean reversion, stochastic volatility, and inverse leverage effect as well as dependencies between commodities. In this paper we derive the forward price dynamics based on our multivariate spot price model, providing a very flexible structure for the forward curves, including contango, backwardation, and hump shape. Moreover, a Fourier transform-based method to price options on the forward is described.

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Benth, F. E., and L. Vos. "Pricing of Forwards and Options in a Multivariate Non-Gaussian Stochastic Volatility Model for Energy Markets." Advances in Applied Probability 45, no. 02 (2013): 572–94. http://dx.doi.org/10.1017/s0001867800006443.

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Abstract:

In Benth and Vos (2013) we introduced a multivariate spot price model with stochastic volatility for energy markets which captures characteristic features, such as price spikes, mean reversion, stochastic volatility, and inverse leverage effect as well as dependencies between commodities. In this paper we derive the forward price dynamics based on our multivariate spot price model, providing a very flexible structure for the forward curves, including contango, backwardation, and hump shape. Moreover, a Fourier transform-based method to price options on the forward is described.

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Dong, Jun, Xihao Dou, Aruhan Bao, Yaoyu Zhang, and Dongran Liu. "Day-Ahead Spot Market Price Forecast Based on a Hybrid Extreme Learning Machine Technique: A Case Study in China." Sustainability 14, no. 13 (2022): 7767. http://dx.doi.org/10.3390/su14137767.

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With the deepening of China’s electricity spot market construction, spot market price prediction is the basis for making reasonable quotation strategies. This paper proposes a day-ahead spot market price forecast based on a hybrid extreme learning machine technology. Firstly, the trading center’s information is examined using the Spearman correlation coefficient to eliminate characteristics that have a weak link with the price of power. Secondly, a similar day-screening model with weighted grey correlation degree is constructed based on the grey correlation theory (GRA) to exclude superfluous

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Pani, Upananda, Ştefan Cristian Gherghina, Mário Nuno Mata, Joaquim António Ferrão, and Pedro Neves Mata. "Does Indian Commodity Futures Markets Exhibit Price Discovery? An Empirical Analysis." Discrete Dynamics in Nature and Society 2022 (March 8, 2022): 1–14. http://dx.doi.org/10.1155/2022/6431403.

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Price discovery function analyses the dynamics of futures and spot price behavior in an asset’s intertemporal dimensions. The present study examines the price discovery function of the bullion, metal, and energy commodity futures and spot prices through the Granger causality and Johansen–Juselius cointegration tests. The Granger causality test results show bidirectional causality between the spot and futures returns for gold, silver, aluminum, lead, nickel, and zinc. The Johansen cointegration test shows that spot and futures prices are in the long-run equilibrium path for silver, aluminum, le

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Vedran Uran. "MATHEMATICAL MODEL OF THE ELECTRICITY PRICES ON THE SPOT MARKET." Journal of Energy - Energija 55, no. 2 (2023): 202–17. http://dx.doi.org/10.37798/2006552386.

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The price on the electricity market is constantly changing. Owing to the characteristics of electricity market the future movement of the price is relatively hard to predict. For this reason the following three processes are applied: the process of the future electricity price movement according to the geometric Brownian motion, the mean reversion process, and the price spikes process. The paper discusses all three processes, including their definitions, formulas and applications, as well as their upsides and downsides.

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Monteiro, Claudio, Ignacio J. Ramirez-Rosado, and L. Alfredo Fernandez-Jimenez. "A strategy for electricity buyers in futures markets." E3S Web of Conferences 152 (2020): 03007. http://dx.doi.org/10.1051/e3sconf/202015203007.

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This paper presents an original trading strategy for electricity buyers in futures markets. The strategy applies a medium-term electricity price forecasting model to predict the monthly average spot price which is used to evaluate the Risk Premium for a physical delivery under a monthly electricity futures contract. The proposed trading strategy aims to provide an advantage relatively to the traditional strategy of electricity buyers (used as benchmark), anticipating the good/wrong decision of buying electricity in the futures market instead in the day-ahead market. The mid-term monthly averag

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Shao, Li-Peng, Jia-Jia Chen, Lu-Wen Pan, and Zi-Juan Yang. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions." Mathematics 10, no. 23 (2022): 4420. http://dx.doi.org/10.3390/math10234420.

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This paper addresses the deregulated electricity market arising in a distribution system with an electricity transaction. Under such an environment, the distribution system operator (DSO) with a distributed generator faces the challenge of electricity price uncertainty in a spot market. In this context, a credibility theory-based robust optimization model with multiple transactions is established to hedge the uncertain spot price of the DSO. Firstly, on the basis of credibility theory, the spot price is taken as a fuzzy variable and a risk aversion-based fuzzy opportunity constraint is propose

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Kang, Seok Kyu. "The Unbiasedness and Hedging Effectiveness in KOSPI200 Futures Market." Journal of Derivatives and Quantitative Studies 15, no. 1 (2007): 73–100. http://dx.doi.org/10.1108/jdqs-01-2007-b0003.

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This study is to examine the unblasedness hypothesis and hedging effectiveness in KOSPI20() futures market. The unbiasedness and efficiency hypothesis is carried out using a cointegration methodology. And hedging effectiveness is measured by comparing hedging performance of the naive hedge model, OLS hedge model. and constant correlation bivariate GARCH (1. 1) hedge model based on rolling windows. The sample period covers from May. 3. 1996 to December. 8, 2005. The empirical results are summarized as follows: First, there exists the cOintegrating relationship between realized spot prices and f

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Wu, Congxin, Xinyu Wang, Shan Luo, Jing Shan, and Feng Wang. "Influencing Factors Analysis of Crude Oil Futures Price Volatility Based on Mixed-Frequency Data." Applied Sciences 10, no. 23 (2020): 8393. http://dx.doi.org/10.3390/app10238393.

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This article takes into account the form of mixed data as well as the peak and thick tail characteristics contained in the data characteristics, expands the GARCH-MIDAS (Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling) model, establishes a new GARCH-MIDAS model with the residual term of the skewed-t distribution, and analyzes the influence factors of crude oil futures price volatility, which can better explain the changing laws of crude oil price volatility. The results show the following: First, the low-frequency factors include crude oil production, consumption,

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Mallika, Mathew, and M. M. Sulphey. "Gold Exchange Traded Fund - Price Discovery and Performance Analysis." Scientific Annals of Economics and Business 65, no. 4 (2018): 477–95. http://dx.doi.org/10.2478/saeb-2018-0024.

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Abstract The paper aims to examine the price discovery process and the performance of Gold Exchange Traded Funds especially with respect to two Gold ETFs, namely, Goldman Sachs Gold Exchange Traded Scheme (GoldBeEs) and SBI Gold Exchange Traded Scheme (SBIGETS), for the period 2009 – 2016. The study has employed Johansen cointegration and Johansen’s Vector Error Correction Model (VECM) for the price discovery analysis. The results of VECM reveal that the spot prices lead the Gold ETFs price during the study period. Tracking Error analysis shows that Gold ETFs have neither outperformed nor unde

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Heng, Wang, and Xu Qi. "Procurement Strategies Using Portfolio Approach Based on Options and Spot Markets Procurement." International Journal of Business and Management 12, no. 10 (2017): 212. http://dx.doi.org/10.5539/ijbm.v12n10p212.

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The paper explored the conditions for retailers to implement option contract and the strategies to make joint purchase in spot market. Under the condition of uncertain market demands, a joint purchase model integrating batch ordering, option contract and spot market has been developed. Considering price fluctuation, the conditions for implementing option contract-based ordering have been studied; the impacts of price fluctuation and option execution price on retailers optimal ordering of joint purchase have been analyzed as well. The result shows that if a retailer adopts a joint purchase stra

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Dang-Nguyen, S., and Y. Rakotondratsimba. "Control of price acceptability under the univariate Vasicek model." International Journal of Financial Engineering 03, no. 03 (2016): 1650014. http://dx.doi.org/10.1142/s2424786316500146.

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The valuation of the probability of a financial contract to be lower or higher than a given price under the univariate Vasicek model is discussed in this paper. This price restriction can be justified by consistency reasons, since some prices may not be coherent on a financial point of view, e.g. they imply negative yields, or thought as unreachable by the asset manager. At first, assuming that the pricing functions is monotone, the price constraints are formulated in terms of a threshold on the value of the spot rate process. Since this process is Gaussian, these limits are reformulated in te

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Qin, Jieye, Christopher J. Green, and Kavita Sirichand. "Spot–Futures Price Adjustments in the Nikkei 225: Linear or Smooth Transition? Financial Centre Leadership or Home Bias?" Journal of Risk and Financial Management 16, no. 2 (2023): 117. http://dx.doi.org/10.3390/jrfm16020117.

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This paper studies price discovery in Nikkei 225 markets through the nonlinear smooth transition price adjustments between spot and future prices and across all three futures markets. We test for smooth transition nonlinearity and employ an exponential smooth transition error correction model (ESTECM) with exponential generalised autoregressive conditional heteroscedasticity (EGARCH), allowing for the effects of transaction costs, heterogeneity, and asymmetry in Nikkei price adjustments. We show that the ESTECM-EGARCH is the appropriate model as it offers new insights into Nikkei price dynamic

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Lin, Ching-Chung, Shen-Yuan Chen, Dar-Yeh Hwang, and Chien-Fu Lin. "Does Index Futures Dominate Index Spot? Evidence from Taiwan Market." Review of Pacific Basin Financial Markets and Policies 05, no. 02 (2002): 255–75. http://dx.doi.org/10.1142/s021909150200078x.

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By utilizing vector error correction model (VECM) and EGARCH model, this article uses 5-minute intraday data to examine the interaction of return and volatility between Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the newly introduced TAIEX futures. VECM model shows that there exists bi-directional Granger causality between index spot and index futures markets, but spot market plays a more important role in price discovery. The results of impulse response function and information share indicate that most of the price discovery happens in index spot market. The evidence

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