An Application of Marshall-Edgeworth Spot Price Index in Wind-Thermal Generation Swap Option Pricing

2019 ◽  
Author(s):  
Zhixiong Hu ◽  
Ming Zhou ◽  
Zhiming Jiang ◽  
Yan Zhan ◽  
Xiaojuan Liu
Keyword(s):  
Option Pricing ◽  
Price Index ◽  
Spot Price ◽  
Thermal Generation

scholarly journals Dynamic Nonlinear Correlation Studies on Stock and Oil Market Based on Copula

2015 ◽  
Vol 8 (1) ◽  
pp. 405-409
Author(s):  
He Xin ◽  
Zhang Guofu
Keyword(s):  
Change Point ◽  
Stock Price ◽  
Price Index ◽  
Tail Dependence ◽  
Spot Price ◽  
Copula Model ◽  
Correlation Studies ◽  
Oil Market ◽  
Sample Range ◽  
Stock Price Index

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 and stock price index shows irregular fluctuation.

An Option Pricing Model Based on a Renewable Energy Price Index

Energy ◽  
2021 ◽  
pp. 122117
Author(s):  
Jian XUE ◽  
Jing DING ◽  
Laijun ZHAO ◽  
Di ZHU ◽  
Lei LI
Keyword(s):  
Renewable Energy ◽  
Option Pricing ◽  
Price Index ◽  
Energy Price ◽  
Pricing Model ◽  
Model Based ◽  
Option Pricing Model

scholarly journals Modelling Electricity Futures by Ambit Fields

2014 ◽  
Vol 46 (03) ◽  
pp. 719-745 ◽  
Author(s):  
Ole E. Barndorff-Nielsen ◽  
Fred Espen Benth ◽  
Almut E. D. Veraart
Keyword(s):  
Option Pricing ◽  
Futures Markets ◽  
Spot Price ◽  
Regularity Conditions ◽  
Change Of Measure ◽  
New Model ◽  
Modelling Framework ◽  
Model Class

In this paper we propose a new modelling framework for electricity futures markets based on so-calledambit fields. The new model can capture many of the stylised facts observed in electricity futures and is highly analytically tractable. We discuss martingale conditions, option pricing, and change of measure within the new model class. Also, we study the corresponding model for the spot price, which is implied by the new futures model, and show that, under certain regularity conditions, the implied spot price can be represented in law as a volatility modulated Volterra process.

Price discovery and volatility spillovers in futures and spot commodity markets

2014 ◽  
Vol 11 (2) ◽  
pp. 211-226 ◽  
Author(s):  
Mantu Kumar Mahalik ◽  
Debashis Acharya ◽  
M. Suresh Babu
Keyword(s):  
Price Index ◽  
Price Discovery ◽  
Commodity Prices ◽  
Spot Market ◽  
Commodity Markets ◽  
Spot Price ◽  
Future Price ◽  
Reverse Causality ◽  
Content Type ◽  
Volatility Spillovers

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 commodity index (LCOMDEXFP) effectively serve the price discovery function in the spot market implying that there is a flow of information from future to spot commodity markets but the reverse causality does not exist. There is no cointegrating relationship between metal future price index (LMETALFP) and metal spot price index (LMETALSP). Besides the bivariate EGARCH model indicates that although the innovations in one market can predict the volatility in another market, the volatility spillovers from future to the spot market are dominant in the case of LENERGY and LCOMDEX index while LAGRISP acts as a source of volatility toward the agri-futures market. Research limitations/implications – The results are aggregate in nature. Further study at disaggregated level will provide further insights on behavior of specific commodity prices and the price discovery process. Originality/value – The paper provides useful information about the evolution and structures of futures commodity trading in India, related literature and relevant methodology concerning the hypotheses.

scholarly journals Modelling Electricity Futures by Ambit Fields

2014 ◽  
Vol 46 (3) ◽  
pp. 719-745 ◽  
Author(s):  
Ole E. Barndorff-Nielsen ◽  
Fred Espen Benth ◽  
Almut E. D. Veraart
Keyword(s):  
Option Pricing ◽  
Futures Markets ◽  
Spot Price ◽  
Regularity Conditions ◽  
Change Of Measure ◽  
New Model ◽  
Modelling Framework ◽  
Model Class

In this paper we propose a new modelling framework for electricity futures markets based on so-called ambit fields. The new model can capture many of the stylised facts observed in electricity futures and is highly analytically tractable. We discuss martingale conditions, option pricing, and change of measure within the new model class. Also, we study the corresponding model for the spot price, which is implied by the new futures model, and show that, under certain regularity conditions, the implied spot price can be represented in law as a volatility modulated Volterra process.

scholarly journals BRANCHING PARTICLE PRICERS WITH HESTON EXAMPLES

2020 ◽  
Vol 23 (01) ◽  
pp. 2050003 ◽  
Author(s):  
MICHAEL A. KOURITZIN ◽  
ANNE MACKAY
Keyword(s):  
Monte Carlo ◽  
Option Pricing ◽  
Importance Sampling ◽  
Particle Filtering ◽  
Sequential Monte Carlo ◽  
Heston Model ◽  
Spot Price ◽  
Monte Carlo Algorithms ◽  
Effective Particle ◽  
Path Dependent

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and volatility, especially for purposes of path-dependent option pricing. The resulting simulation algorithm is an analog to the weighted particle filtering algorithm that might be improved by resampling or branching. Indeed, some branching algorithms are shown herein to improve pricing performance substantially while some resampling algorithms are shown to be less suitable in certain cases. A historical property is given and explained as the distinguishing feature between the sequential Monte Carlo algorithms that work on path-dependent option pricing and those that do not. In particular, it is recommended to use the so-called effective particle branching algorithm within importance-sampling Monte Carlo methods for path-dependent option pricing. All recommendations are based upon numeric comparison of option pricing problems in the Heston model.

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

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