Pricing Mining Concessions Based on Combined Multinomial Pricing Model

A combined multinomial pricing model is proposed for pricing mining concession in which the annualized volatility of the price of mineral products follows a multinomial distribution. First, a combined multinomial pricing model is proposed which consists of binomial pricing models calculated according to different volatility values. Second, a method is provided to calculate the annualized volatility and the distribution. Third, the value of convenience yields is calculated based on the relationship between the futures price and the spot price. The notion of convenience yields is used to adjust our model as well. Based on an empirical study of a Chinese copper mine concession, we verify that our model is easy to use and better than the model with constant volatility when considering the changing annualized volatility of the price of the mineral product.

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Research on Option Pricing Model under Uncertainty

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.3156 ◽

2014 ◽

Vol 513-517 ◽

pp. 3156-3159

Author(s):

Kun Long Zhang ◽

Li Xia Song

Keyword(s):

Empirical Study ◽

Option Pricing ◽

Financial Market ◽

Price Change ◽

Asset Price ◽

Pricing Model ◽

Pricing Models ◽

Uncertain Environments ◽

Option Pricing Model ◽

Behavior Choice

In the real financial market, there are always other uncertain phenomena, such as fuzzy phenomenon, random phenomenon. Along with empirical study increasing investigator discovered that this kind of uncertainty affects policy-maker's behavior choice and the asset price change. Researcher pay more and more attention to the problems on the option pricing under in uncertain environments, Therefore, the paper shows that options can be valued successfully in uncertain environments, some option pricing models are established, the corresponding algorithm is designed to solve these models.

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A Study on the Causal Relationship between Spot Price and Futures Price of Crude Oil and Agricultural Products

International Journal for Innovation Education and Research ◽

10.31686/ijier.vol8.iss5.2345 ◽

2020 ◽

Vol 8 (5) ◽

pp. 296-315

Author(s):

Dong Hoon Shin ◽

Seon Hyeon Kim

Keyword(s):

Causal Relationship ◽

Futures Market ◽

Agricultural Products ◽

Spot Price ◽

Agricultural Product ◽

Causality Test ◽

Futures Price ◽

Derivatives Markets ◽

The Relationship ◽

Toda And Yamamoto

This paper studies the relationship between the agricultural, energy, and derivatives markets. This study empirically analyzes how the results of previous studies on the Granger causality between oil price and the spot price of agricultural products appear in the futures market by using the Toda and Yamamoto (1995)’ causality test. There are two main findings. First, 7 bidirectional causalities and 27 causalities between oil and 6 agricultural products are found, providing strong evidence of a causal relationship. Second, causality is found between oil prices and grain and oilseed type agricultural products, and the spot price of oil has relatively more causalities on agricultural product prices than the futures price of oil. Lastly, testing each period shows that a financial crisis can strengthen the relationship between the agriculture markets and the energy markets

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Research on the Relationship between Iron Ore Futures Price and Spot Price in China

Proceedings of the 2018 International Conference on Social Science and Education Reform (ICSSER 2018) ◽

10.2991/icsser-18.2018.85 ◽

2018 ◽

Author(s):

Hui Sheng

Keyword(s):

Iron Ore ◽

Spot Price ◽

Futures Price ◽

The Relationship

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MODEL ASSET PRICING YANG BERLAKU DI INDONESIA: STUDY KASUS SAHAM UNGGULAN

J-MAS (Jurnal Manajemen dan Sains) ◽

10.33087/jmas.v3i2.52 ◽

2018 ◽

Vol 3 (2) ◽

pp. 146

Author(s):

Yunan Surono

Keyword(s):

Standard Deviation ◽

Asset Pricing ◽

Stock Market ◽

Stock Prices ◽

Stock Return ◽

Explanatory Power ◽

Influential Factors ◽

Pricing Model ◽

Pricing Models ◽

Better Than

This study tested the influential factors in the estimation of stock return and compare the three models of asset pricing, i.e., Capital Asset Pricing Model, Three Factors Pricing models, and Four Factors Pricing Model. The purpose of this research is to obtain a model of asset pricing can provide estimated stock return with better among three types of models. The research sample is stocks LQ45 in Indonesia stock exchange (idx) during the period of 2005-2016. Regression analysis performed on variables, excess return market, size, book to market, and momentum is against the return of the monthly stocks fit each model to know the influence of variables and the feasibility of the model with the adjusted R square. Different test ANOVA is performed to obtain the standard deviation of each model and difference significance between the three models. The results showed: (1) factors in excess of market return, size premium, value premium, and momentum factors effect on stock return, (2) based on independent variables constituting influence, CAPM, Three Factors Pricing models or Four Factors Pricing Model can capture the behavior of stock prices on issuers who are members of group LQ45 on Indonesia stock market, (3) based on the adjusted R Square and standard deviation, Three Factors Pricing Model better than the CAPM and the Four Factors Pricing Model better than Three Factors Pricing Model, but all three models have a weak explanatory power as well as the results of significance of difference test that is not significant, so that the benefits of these models to estimated return expectations of stock market Indonesia is still questionable.

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